In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey calculated four land cover basin characteristics rasters from the National Land Cover Database (NLCD) 2019 as part of updating the South Carolina StreamStats application. These datasets are raster representations of impervious surface, developed, forested, and storage land cover attributes within the South Carolina StreamStats study area, and will be served in the South Carolina StreamStats application to describe delineated watersheds. The StreamStats application provides access to spatial analytical tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface can be used to delineate watershed areas, get basin characteristics and estimates of flow statistics, and more.

In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey prepared a geospatial raster dataset describing impervious surface in the SC StreamStats study area derived from the 30m resolution National Land Cover Dataset (NLCD) 2019. This layer, which covers the SC StreamStats study area, has been resampled from the source resolution to a scale of 30ft pixels and reprojected to the common projection of the other project data layers (SC State Plane NAD 1983 International Feet WKID 2273). It will be served as part of the SC StreamStats application (https://streamstats.usgs.gov) to describe delineated watersheds. The StreamStats application provides access to spatial analytical tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based interface can be used to delineate watershed areas, get basin characteristics and estimates of flow statistics, and more.

The U.S. Geological Survey (USGS) has calculated over 25 different basin characteristics as part of preparing the West Virginia StreamStats 2021 application. These datasets are raster representations of various environmental, geological, and land use attributes within the West Virginia StreamStats 2021 study area. This study area was defined by Watershed Boundary HUC 8 digital data, and as such there is an area of about 70 square miles in the SE corner of WV is not included in these raster datasets as it drains towards Virginia. The basin characteristics data will be served in the West Virginia StreamStats 2021 application used to describe delineated watersheds. The StreamStats application provides access to spatial analytical tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface can be used to delineate drainage areas, get basin characteristics, and estimates of flow statistics for data-collection stations and user-selected ungaged sites.

This dataset was produced by the US Geological Survey as a supporting dataset to be used for the purpose of calculating stream gage basin characteristics in preparation for the South Carolina StreamStats application. This integer raster dataset represents runoff curve numbers for the combinations of hydrological soils groupings and land cover types within the South Carolina StreamStats study area. Soils data were from the USDA, NRCS SSURGO soils database and land cover data are USGS 2019 NLCD data. The dataset will be used in peak flow regression equations that are used to predict flow in South Carolina streams. The StreamStats application provides access to spatial analytical tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface of StreamStats can be used to delineate drainage areas, get basin characteristics, estimates of flow statistics, and more. Inventory of data release: SC_RCN_LU_CO.tiff (1 .tif file): Cloud optimized GeoTIFF containing integer rasters that are runoff curve numbers for soils/land cover combinations

The U.S. Geological Survey (USGS), in cooperation with the New Jersey Department of Environmental Protection (NJDEP), calculated several basin characteristics as part of the updated New Jersey StreamStats 2022 application (U.S. Geological Survey, 2022). These datasets are raster representations of various environmental, geological, and land use attributes within the New Jersey StreamStats 2022 study area; they are applied in the New Jersey 2022 application to describe delineated watersheds. This update features improvements in base elevation resolution from 10 meters to 10 feet and stream centerline hydrography from 1:24,000 to 1:2,400, as well as resampling of previously existing datasets to match the 10-foot resolution. The sixteen 8-digit Watershed Boundary Dataset Hydrologic Unit Codes (HUCs) represented by these datasets are 02020007, 02030103, 02030104, 02030105, 02040101, 02040102, 02040103, 02040104, 02040105, 02040106, 02040201, 02040202, 02040203, 02040206, 02040301, and 02040302 (U.S. Geological Survey, 2016). The StreamStats application provides access to spatial analytical tools that are useful for water-resources planning and management, as well as engineering and design purposes. The map-based user interface can be used to delineate drainage areas, determine basin characteristics and estimate flow statistics, including instantaneous flood discharge, monthly flow-duration, and monthly low-flow frequency statistics for ungaged streams. References cited: U.S. Geological Survey, 2016, National Hydrography: U.S. Geological Survey, accessed February 7, 2022, at https://www.usgs.gov/national-hydrography. U.S. Geological Survey, 2022, StreamStats v4.6.2: U.S. Geological Survey, accessed February 7, 2022, at https://streamstats.usgs.gov/ss/.

This dataset contains an inventory of South Carolina U.S. Geological Survey (USGS) streamgages evaluated in 2017 as part of gage network gap assessment. Both continuous record and crest stage gages are included in this dataset. The data are grouped into three categories: rural streamgages with equal to or greater than 10 years of peak-flow data, rural streamgages with less than 10 years of peak-flow data, and urban streamgages.

In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey (USGS) updated the foundational geospatial layers for the South Carolina StreamStats web application (https://www.usgs.gov/streamstats), which provides analytical tools useful for water-resources planning and management (Kolb and others, 2018). This dataset comprises the 45 local geodatabases of the 8-digit Hydrologic Unit Code (HUC-8) watersheds in the South Carolina StreamStats (henceforth referred to as SC StreamStats) study area along with the global geodatabase that ties the local HUC-8s together. This dataset supersedes the previous SC StreamStats version 1 data published in Kolb and others (2018), reflecting updated lidar-derived elevation data for much of the state, along with new streamlines for Charleston and Georgetown counties.

In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey updated the foundational geospatial layers for the South Carolina StreamStats web application (https://water.usgs.gov/osw/streamstats/), which provides analytical tools useful for water-resources planning and management (Kolb and others, 2018). This dataset presents the digital elevation model, lidar-derived flow direction, flow accumulation, and percent basin slope raster data layers used for analysis in StreamStats. It also includes the streamline vector data used to hydro-enforce the raster data layers.

This dataset consists of raster geotiff outputs of annual map projections of land use and land cover for the California Central Valley for the period 2011-2101 across 5 future scenarios. Four of the scenarios were developed as part of the Central Valley Landscape Conservation Project. The 4 original scenarios include a Bad-Business-As-Usual (BBAU; high water availability, poor management), California Dreamin’ (DREAM; high water availability, good management), Central Valley Dustbowl (DUST; low water availability, poor management), and Everyone Equally Miserable (EEM; low water availability, good management). These scenarios represent alternative plausible futures, capturing a range of climate variability, land management activities, and habitat restoration goals. We parameterized our models based on close interpretation of these four scenario narratives to best reflect stakeholder interests, adding a baseline Historical Business-As-Usual scenario (HBAU) for comparison. For these future map projections, the model was initialized in 2011 and run forward on an annual time step to 2101. Each filename has the associated scenario ID (scn418 = DUST, scn419 = DREAM, scn420 = HBAU, scn421 = BBAU, and scn426 = EEM), State Class identification as “sc”, model iteration (= it1 in all cases as only 1 Monte Carlo simulation was modeled), and timestep as “ts” information embedded in the file naming convention. For example, the filename scn418.sc.it1.ts2027.tif represents the DUST scenario (scn418), state class information (sc), iteration 1 (it1), for the 2027 model year (ts2027). The full methods and results of this research are described in detail in the parent manuscript "Integrated modeling of climate, land use, and water availability scenarios and their impacts on managed wetland habitat: A case study from California’s Central Valley" (2021).

This dataset was produced in by the Delaware Geological survey in cooperation with the US Geological Survey and Delaware Department of Transportation for the purpose of calculating stream gage basin characteristics in preparation for the Delaware 2020 StreamStats application. These datasets are raster representations of various environmental, geological, and land use attributes within the Delaware StreamStats 2020 study area, and will be served in the Delaware StreamStats 2020 application to describe delineated watersheds. The StreamStats application provides access to spatial analytical tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface can be used to delineate drainage areas, get basin characteristics and estimates of flow statistics, and more.