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This dataset provides timeseries data on water quality and quantity, as collected or computed from outside sources. The format is many tables with one row per time series observation (1 tab-delimited file per site-variable combination, 1 zip file per site). This compilation of data is intended for use in estimating or interpreting metabolism. Sites were included if they met the initial criteria of having at least 100 dissolved oxygen observations and one of the accepted NWIS site types ('ST','ST-CA','ST-DCH','ST-TS', or 'SP'). This dataset is part of a larger data release of metabolism model inputs and outputs for 356 streams and rivers across the United States (https://doi.org/10.5066/F70864KX). The complete release...
This data release component contains model inputs including river basin attributes, weather forcing data, and simulated and observed river discharge.
Monthly Aquaculture and Irrigation Water-Use Estimates for the Mississippi Alluvial Plain, 1999-2017
These monthly water-use rasters estimate the total amount of groundwater used for aquaculture and irrigation purposes within the Mississippi Alluvial Plain during the growing season (April-October). This dataset contains 133 monthly water-use rasters that are totals of 6 different categories: aquaculture, cotton, corn, rice, soybeans, and all other crops. Units are in cubic meters per square mile. Aquaculture and irrigation water-use estimates are included in this data release in two different formats: georeferenced TIFFs (GeoTIFFs) for simple viewing and geospatial operations and a network common data form (NetCDF) for use in modeling applications and with each month as a separate raster array table.
These monthly water-use rasters estimate the total amount of groundwater used for aquaculture and irrigation purposes within the Mississippi Alluvial Plain during the growing season (April-October). This dataset contains 798 monthly water-use rasters for 6 different categories: aquaculture, cotton, corn, rice, soybeans, and all other crops. Units are in cubic meters per square mile.
The annual water-use rasters estimate the total amount of groundwater used for aquaculture and irrigation purposes within the Mississippi Alluvial Plain. This dataset contains 19 annual water-use rasters that are totals of 6 different use categories: aquaculture, cotton, corn, rice, soybeans, and all other crops. Units are in cubic meters per square mile.
The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in dense time series of Landsat image stacks to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm makes use of predictors derived from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions. Outputs of the BAECV algorithm consist of pixel-level burn probabilities for each Landsat scene, and annual burn probability, burn classification, and burn date composites. These products were generated for the conterminous United States for 1984 through 2015. These data are also available for download at https://rmgsc.cr.usgs.gov/outgoing/baecv/BAECV_CONUS_v1.1_2017/...
The U.S. Geological Survey (USGS) has been engaged in airborne electromagnetics (AEM) since the 1970s, playing a role in the development of early acquisition systems, developing calibration methods, refining standards for data acquisition, improving data processing, modeling, and interpretation methods, and expanding the range of AEM applications. However, USGS AEM survey visibility and data accessibility has not advanced as rapidly as our use of the technique. This data release catalogs AEM surveys in the United States that have contributed to studies under USGS programs including Water, Geologic Mapping, Minerals, Energy, Environmental Health, Ecosystems, Hazards, and Climate. This dataset contains locations for...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Alabama,
Arizona,
Arkansas,
California,
Colorado,
Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria are met. This dataset contains results from a study examining the potential impacts of projected climatic change on prescribed burning in the southeastern United States. A set of burn window criteria (suitable weather conditions within which burning may occur based on maximum daily temperature, daily average relative humidity, and daily average wind speed), were applied to projections from an ensemble of Global Climate Models (GCM) under two greenhouse gas emission scenarios, as well as past observations for comparison. Data are...
Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria are met. This dataset contains results from a study examining the potential impacts of projected climatic change on prescribed burning in the southeastern United States. A set of burn window criteria (suitable weather conditions within which burning may occur based on maximum daily temperature, daily average relative humidity, and daily average wind speed), were applied to projections from an ensemble of Global Climate Models (GCM) under two greenhouse gas emission scenarios, as well as past observations for comparison. Data are...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Arkansas,
Florida,
Georgia,
Kentucky,
Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria are met. This dataset contains results from a study examining the potential impacts of projected climatic change on prescribed burning in the southeastern United States. A set of burn window criteria (suitable weather conditions within which burning may occur based on maximum daily temperature, daily average relative humidity, and daily average wind speed), were applied to projections from an ensemble of Global Climate Models (GCM) under two greenhouse gas emission scenarios, as well as past observations for comparison. Data are...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Arkansas,
Florida,
Georgia,
Kentucky,
Near-surface site characteristics are critical for accurately modeling ground motion, which in turn influences seismic hazard analysis and design of critical infrastructure. Currently, there are many strong motion accelerometers within the Advanced National Seismic System (ANSS) that are missing this information. We use a Geographic Information Systems (GIS) based framework to intersect the site coordinates of approximately 5,500 ANSS accelerometers located throughout the United States and its territories with geology and velocity information. We consider: (1) surficial geology from digitized geologic maps (Horton, 2017; Wilson et al., 2015; Sherrod et al., 2007; Bawiec, 1999; Saucedo, 2005; Bedrossian et al., 2012;...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANSS,
Alabama,
American Samoa,
Arizona,
Arkansas,
Concentrations of inorganic constituents, dissolved organic carbon (DOC), tritium, per- and polyfluoroalkyl substances (PFAS), volatile organic compounds (VOCs), and pharmaceuticals were measured in groundwater samples collected from 254 wells in 2019 and 2020. Concentrations of inorganic constituents, DOC, VOCs, and pharmaceuticals were measured at the U.S. Geological Survey (USGS) National Water Quality Laboratory in Lakewood, Colorado. Concentrations of tritium were measured at the USGS Tritium Laboratory in Menlo Park, California. Concentrations of PFAS were measured at SGS Laboratory in Orlando, Florida. In addition, several geospatial parameters were determined, including: percentages of selected land uses...
Prior research has shown that sediment budgets, and therefore stability, of microtidal marsh complexes scale with areal unvegetated to vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. This effort has developed the UVVR metric using readily available satellite imagery for the coastal areas of the contiguous United States (CONUS). These datasets provide annual averages of 1) developed, 2) vegetated, 3) unvegetated ratios and 4) an unvegetated to vegetated ratio (UVVR) at 30-meter resolution over the coastal areas of the contiguous United States for the years 2014-2018. Additionally, multi-year average values of vegetated ratio, its standard...
Prior research has shown that sediment budgets, and therefore stability, of microtidal marsh complexes scale with areal unvegetated to vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. This effort has developed the UVVR metric using readily available satellite imagery for the coastal areas of the contiguous United States (CONUS). These datasets provide annual averages of 1) developed, 2) vegetated, 3) unvegetated ratios and 4) an unvegetated to vegetated ratio (UVVR) at 30-meter resolution over the coastal areas of the contiguous United States for the years 2014-2018. Additionally, multi-year average values of vegetated ratio, its standard...
These data were used to quantify land area change in a wetlands possible zone of coastal wetlands during a 1985-2020 observation period. The datasets presented in this data release represent annual median estimates of the fractional amount of land, floating aquatic vegetation, submerged aquatic vegetation, and water per Landsat pixel. These data are intended for coarse-scale analysis of wetland change area. The datasets are summarized by 10-digit Hydrologic Unit Code (HUC10), and land area change through time is fit using a penalized regression smooth spline. The trends are therefore generalized in time and are intended to present coarse scale observations of trends in wetland area change.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Conterminous United States,
Florida,
Gulf of Mexico Coast,
Louisiana,
These data were used to quantify land area change in a wetlands possible zone of coastal wetlands during a 1985-2020 observation period. The datasets presented in this data release represent annual median estimates of the fractional amount of land, floating aquatic vegetation, submerged aquatic vegetation, and water per Landsat pixel. These data are intended for coarse-scale analysis of wetland change area. The datasets are summarized by 10-digit Hydrologic Unit Code (HUC10), and land area change through time is fit using a penalized regression smooth spline. The trends are therefore generalized in time and are intended to present coarse scale observations of trends in wetland area change.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Conterminous United States,
Florida,
Gulf of Mexico Coast,
Louisiana,
These data were used to quantify land area change in a wetlands possible zone of coastal wetlands during a 1985-2020 observation period. The datasets presented in this data release represent annual median estimates of the fractional amount of land, floating aquatic vegetation, submerged aquatic vegetation, and water per Landsat pixel. These data are intended for coarse-scale analysis of wetland change area. The datasets are summarized by 10-digit Hydrologic Unit Code (HUC10), and land area change through time is fit using a penalized regression smooth spline. The trends are therefore generalized in time and are intended to present coarse scale observations of trends in wetland area change.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Conterminous United States,
Florida,
Gulf of Mexico Coast,
Louisiana,
This child item describes Python code used to estimate average yearly and monthly tourism per 1000 residents within public-supply water service areas. Increases in population due to tourism may impact amounts of water used by public-supply water systems. This data release contains model input datasets, Python code used to develop the tourism information, and output estimates of tourism. 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. Output from this code was used as an input feature in the public supply delivery and water use machine learning models. This page includes the following files: tourism_input_data.zip...
This child item describes a public supply delivery machine learning model that was developed to estimate public-supply deliveries. Publicly supplied water may be delivered to domestic users or to commercial, industrial, institutional, and irrigation (CII) users. This model predicts total, domestic, and CII per capita rates for public-supply water service areas within the conterminous United States for 2009-2020. This child item contains model input datasets, code used to build the delivery machine learning model, and national predictions. 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. This page includes the following...
This child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. 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. Data retrieved by the census data collector code were used as input...
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