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Note: this data release has been deprecated. Please see new data release here: https://doi.org/10.5066/P9RC7RJM. The U.S. Geological Survey Oregon Water Science Center, in cooperation with The Klamath Tribes initiated a project to understand changes in the surface-water extent of Klamath Marsh, Oregon and changes in groundwater levels within and surrounding the marsh. The initial phase of the study focused on developing datasets needed for future interpretive phases of the investigation. This data release documents the creation of a geospatial dataset of January through May maximum surface-water extent based on a model developed by John Jones (2015; 2019) to detect surface-water inundation within vegetated areas...
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This dataset provides the estimated number of people using publicly supplied groundwater (PSg) or publicly supplied surface water (PSs) for each county in the conterminous U.S. The county boundaries, the PSg, and the PSs represent the year 2010
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This U.S. Geological Survey (USGS) data release consists of data from two tracer investigations in the Snake Creek drainage of Great Basin National Park, White Pine County, Nevada. The first investigation, occurring from April to September 2019, involved injecting a fluorescein dye tracer below a diversion point in Snake Creek and monitoring 13 sites in the Snake Creek and neighboring Big Wash drainages for presence of the dye. The results of the first investigation were used to select a targeted monitoring location for a second, quantitative investigation. The second investigation, occurring from September 2020 to March 2021, involved injecting two tracers, sodium bromide and fluorescein dye, below the same diversion...
The population using public supply drinking water was mapped in two ways: the census enhanced method (CEM) evenly distributes the population across the census block-group, and the urban land-use enhanced method (ULUEM) distributes the population only to certain urban land use designations in order to more precisely locate public supply users. This dataset consists of the estimated population using public supply surface water distributed across block-groups.
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The dataset includes Escherichia coli concentrations in water and sediment collected by James Fluke in the Middle Rio Grande in Albuquerque, NM, from 2017 to 2018.
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The dataset includes Escherichia coli concentrations collected by the Bosque Ecosystem Monitoring Program in the Middle Rio Grande in Albuquerque, NM, from 2017 to 2020.
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The population using public supply drinking water was mapped in two ways: the census enhanced method (CEM) evenly distributes the population across the census block-group, and the urban land-use enhanced method (ULUEM) distributes the population only to certain urban land use designations in order to more precisely locate public supply users. This dataset consists of the estimated population using public supply groundwater distributed across census block-groups.
The population using public supply drinking water was mapped in two ways: the census enhanced method (CEM) evenly distributes the population across the census block-group, and the urban land-use enhanced method (ULUEM) distributes the population only to certain urban land use designations in order to more precisely locate public supply users. This dataset consists of the total estimated population using public supply surface water and groundwater combined, distributed using the urban land-use enhanced method.
The population using public supply drinking water was mapped in two ways: the census enhanced method (CEM) evenly distributes the population across the census block-group, and the urban land-use enhanced method (ULUEM) distributes the population only to certain urban land use designations in order to more precisely locate public supply users. This dataset consists of the total estimated population using public supply surface water and groundwater combined, distributed across block-groups.
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This data release and model archive provides all data, code, and modelling results used in Topp et al. (2023) to examine the influence of deep learning architecture on generalizability when predicting stream temperature in the Delaware River Basin (DRB). Briefly, we modeled stream temperature in the DRB using two spatially and temporally aware process guided deep learning models (a recurrent graph convolution network - RGCN, and a temporal convolution graph model - Graph WaveNet). The associated manuscript explores how the architectural differences between the two models influence how they learn spatial and temporal relationships, and how those learned relationships influence a model's ability to accurately predict...
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Introduction CONUS404 is a unique, high-resolution hydro-climate dataset appropriate for forcing hydrological models and conducting meteorological analysis over the contiguous United States. CONUS404, so named because it covers the CONtiguous United States for 40 years at 4-km resolution, was produced by the Weather Research and Forecasting (WRF) Model simulations run by National Center for Atmospheric Research (NCAR) as part of a collaboration with the U.S. Geological Survey (USGS) Water Mission Area. In fact, CONUS404 includes 41 years of data (water years 1980-2020) and the spatial domain extends beyond the CONUS into Canada and Mexico, thereby capturing transboundary river basins and covering all contributing...
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The dataset includes Escherichia coli concentrations collected by Isleta Pueblo in the Middle Rio Grande in Albuquerque, NM, from 2017 to 2020.
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This dataset provides the calculated proportion of people using publicly supplied groundwater (PSGF) for each county in the conterminous U.S. The county boundaries and the PSGF represent the year 2015.
The population using public supply drinking water was mapped in two ways: the census enhanced method (CEM) evenly distributes the population across the census block-group, and the urban land-use enhanced method (ULUEM) distributes the population only to certain urban land use designations in order to more precisely locate public supply users. This dataset consists of the estimated population using public supply surface water distributed using the urban land-use enhanced method.
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Bathymetric data were collected with a single-beam echosounder in 2022 for 18 selected shallow (0-3 meters) areas to improve a digital elevation model (DEM) for Rainy Lake and Namakan Reservoir created by Environment and Climate Change Canada. Bathymetric data were collected in transects spaced approximately 20 meters apart. In addition to the bathymetric data, the locations and elevations of observed water surface and recovered high-water marks are being provided at select locations because of the high water observed during bathymetric data collection after a spring flood in 2022.
The population using public supply drinking water was mapped in two ways: the census enhanced method (CEM) evenly distributes the population across the census block-group, and the urban land-use enhanced method (ULUEM) distributes the population only to certain urban land use designations in order to more precisely locate public supply users. This dataset consists of the estimated population using public supply groundwater distributed using the urban land-use enhanced method.
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This data release contains input and output data tables from a SPAtially Referenced Regression On Watershed attributes (SPARROW) model, which estimated total nitrogen loads in streams of the Chesapeake Bay watershed under varying better management practice implementation scenarios. Further documentation about the SPARROW modeling framework can be found here: https://pubs.er.usgs.gov/publication/tm6B3. A model archive containing inputs, outputs, code, and helpful spatial data is also included as a zipped folder. This model archive can be used to recreate the output provided in this data release. The model archive includes a read me text file that documents the contents of the archive and how it can be used. SPARROW_Inputs.csv...
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Mitigating the effects of salinity (total dissolved solids) and selenium on water quality in the lower Gunnison River Basin (LGRB) of western Colorado is a major concern for land managers. In cooperation with the Bureau of Reclamation, the U.S. Geological Survey completed a study to develop multiple linear regression models to estimate salinity and selenium loads. The objective of the study was to refine existing models by improving the regressions and using additional geospatial and water-quality data. This data release presents the basin characteristics and loads used to calibrate the models. Also provided are salinity and selenium yield rasters determined by empirical Bayesian kriging of loads estimated by the...
These datasets map the estimated population using public supply drinking water (both groundwater and surface water) using two methods: the census enhanced method (CEM) evenly distributes the population across populated census blocks, and the urban land-use enhanced method (ULUEM) distributes the population only to certain urban land use designations. (See the six Estimated equivalent population using public supply datasets). The estimated number of people using public supply was also computed by county (See Table of estimated county population using public supply dataset). In addition, a polygon dataset was created for the conterminous U.S. that identifies 177 unique Hydrogeologic Mapping Units (HMUs). (See Community...
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Data and preliminary machine-learning models used to predict manganese and 1,4-dioxane in groundwater on Long Island are documented in this data release. Concentration data used to develop the models were from 910 wells for manganese and 553 wells for 1,4-dioxane, primarily public supply wells, from U.S. Geological Survey, U.S. Environmental Protection Agency (USEPA), and Suffolk County Water Authority sources. Thirty-two explanatory variables describe depth, groundwater flow, land use, soil properties, and other features of the aquifer system. The models use XGBoost, an ensemble tree machine learning method. Four models are documented for manganese, predicting the probability of concentrations relative to four...


map background search result map search result map Basin Characteristics and Salinity and Selenium Loads and Yields for Selected Subbasins in the Lower Gunnison River Basin, Western Colorado, 1992─2013 Estimated equivalent population using public supply groundwater in the conterminous United States, CEM Public Supply Groundwater Fraction per County, 2015 Table of Estimated County Population Using Public Supply Groundwater or Surface Water Data and Model Archive for Preliminary Machine Learning Models of Manganese and 1,4-Dioxane in Groundwater on Long Island, New York Klamath Marsh January Through May Maximum Surface Water Extent, 1985-2021 (ver. 2.0, March 2022) Four-kilometer long-term regional hydroclimate reanalysis over the conterminous United States (CONUS), 1979-2020 Data from two tracer investigations in the Snake Creek drainage, Great Basin National Park, White Pine County, Nevada Examining the influence of deep learning architecture on generalizability for predicting stream temperature in the Delaware River Basin SPARROW Model Inputs and Estimated Effects of Agricultural Conservation Practices on Total Nitrogen in Streams of the Chesapeake Bay Watershed Escherichia coli concentrations in the Middle Rio Grande collected by Bosque Ecosystem Monitoring Program, Albuquerque, NM, 2017-2020 Rainy Lake and Namakan Reservoir shallow water bathymetric data, water surface elevations, and recovered high-water marks, 2022 Escherichia coli concentrations in water and sediment in the Middle Rio Grande collected by Fluke, Albuquerque, NM, 2017-2018 Escherichia coli concentrations in the Middle Rio Grande collected by Isleta Pueblo, Albuquerque, NM, 2017-2020 Escherichia coli concentrations in the Middle Rio Grande collected by Isleta Pueblo, Albuquerque, NM, 2017-2020 Data from two tracer investigations in the Snake Creek drainage, Great Basin National Park, White Pine County, Nevada Klamath Marsh January Through May Maximum Surface Water Extent, 1985-2021 (ver. 2.0, March 2022) Rainy Lake and Namakan Reservoir shallow water bathymetric data, water surface elevations, and recovered high-water marks, 2022 Data and Model Archive for Preliminary Machine Learning Models of Manganese and 1,4-Dioxane in Groundwater on Long Island, New York Basin Characteristics and Salinity and Selenium Loads and Yields for Selected Subbasins in the Lower Gunnison River Basin, Western Colorado, 1992─2013 Examining the influence of deep learning architecture on generalizability for predicting stream temperature in the Delaware River Basin SPARROW Model Inputs and Estimated Effects of Agricultural Conservation Practices on Total Nitrogen in Streams of the Chesapeake Bay Watershed Estimated equivalent population using public supply groundwater in the conterminous United States, CEM Table of Estimated County Population Using Public Supply Groundwater or Surface Water Public Supply Groundwater Fraction per County, 2015 Four-kilometer long-term regional hydroclimate reanalysis over the conterminous United States (CONUS), 1979-2020