In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey developed a StreamStats web application (https://water.usgs.gov/osw/streamstats/) that provides analytical tools for water-resources planning and management (Ries and others, 2017). This data set presents the lidar-derived flow direction, flow accumulation, streamline, and hydro-enforced digital elevation model raster data used for analysis in StreamStats. Rasters are included for each of the following hydrologic unit codes (HUCs): 03040101, 03040102, 03040103, 03040104, 03040105, 03040201, 03040202, 03040203, 03040204, 03040205, 03040206, 03040207, 03040208, 03050101, 03050102, 03050103, 03050104, 03050105, 03050106, 03050107, 03050108, 03050109, 03050110, 03050111, 03050112, 03050201, 03050202, 03050203, 03050204, 03050205, 03050206, 03050207, 03050208, 03050209, 03050210, 03060101, 03060102, 03060103, 03060104, 03060105, 03060106, 03060107, 03060108, 03060109, and 03060110. The raster data is organized into four main zip folders, which are called “Flow_Accumulation_Grids,” “Flow_Direction_Grids,” Hydro_Enforced_DEM_Grids,” and “Streamline_Grids.” Reference: Ries, K.G., III, Newson J.K., Smith, M.J., Guthrie, J.D., Steeves, P.A., Haluska, T.L., Kolb, K.R., Thompson, R.F., Santoro, R.D., and Vraga, H.W., 2017, StreamStats, version 4: U.S. Geological Survey Fact Sheet 2017–3046, 4 p., https://doi.org/10.3133/fs20173046.

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.

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.

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

In cooperation with the South Carolina Department of Transportation (SCDOT), the U.S. Geological Survey prepared geospatial layers illustrating the boundaries of the regions used in the South Carolina (SC) Stream Hydrograph Methods presented in Bohman (1990, 1992). The region limits were described in written text and depicted in figures in Bohman (1990,1992), but have not been provided as geospatial layers (due to the age of the original publications). This project used best-available geospatial data from the U.S. Environmental Protection Agency (USEPA) ecoregions (2013) to create equivalent geospatial representations of the Bohman (1990, 1992) region boundaries for the SC Stream Hydrograph Methods. These layers will be used in the SC StreamStats application to generate hydrographs for estimated storm runoff simulations. The StreamStats application (https://streamstats.usgs.gov) 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, retrieve basin characteristics, estimates of flow statistics, and more.

In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey calculated four land cover basin characteristics rasters as part of preparing the South Carolina StreamStats 2021 application. These datasets are raster representations of impervious surface, developed, forested, and storage land cover attributes within the South Carolina StreamStats 2021 study area, and will be served in the South Carolina StreamStats 2021 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 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.

Reliable peak-streamflow information is critical for proper design of stream-related infrastructure, such as bridges, and StreamStats is a Web-based Geographic Information Systems (GIS) application that provides a user-friendly interface to estimate peak flows (https://streamstats.usgs.gov/ss/). StreamStats develops these peak-flow estimates using basin characteristics for the entire contributing area to a user-selected point; however, infrastructure planners often need to estimate flows for an area downstream from a known control such as a reservoir release or a weir. This dataset was compiled in cooperation with the South Carolina Department of Transportation (SCDOT) to provide a GIS layer of filtered regulation points from the U.S. Army Corps Engineers (USACE) National Inventory of Dams and upstream basin polygons for those points, for use within the South Carolina StreamStats client application. A select few characteristics were computed for each basin in the polygon dataset to enable the application to estimate flows above and below each regulation point and better assist SCDOT personnel when designing new or revising existing stream-related infrastructure.

This dataset contains six individual tabular data files. These tabular data files contain measurements of aquatic habitat features and stream channel geomorphology from 20 sites in the Piedmont and Upper Coastal Plain physiographic regions of South Carolina. Specifically, the dataset titled "bedform_slope" contains enumeration of occurrence of bedforms, or macro-habitat features, and streambed and culvert bottom slopes. The dataset titled "culvert_characteristics" contains measurements and descriptions of the culverts. The dataset titled "large_woody_debris" contains measurements and classification of individual pieces of wood included in the assessment. The dataset titled "site_level_information" contains location information for the study site and naming conventions between different databases. The dataset titled "streambed_particle_size" contains measurements of individual bed sediment particles. The dataset titled "transect_scale_data" contains measurements that occurred at 22 transects at each site. Measurements included: stream channel width and depth, streamflow velocity, canopy cover, and other categorical observations.

In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this geologic framework and identifying the transport pathways and sinks of sediment, geoscientists are developing conceptual models of the present-day physical processes shaping the South Carolina coast. The primary objectives of this research effort are: 1) to provide a regional synthesis of the shallow geologic framework underlying the coastal upland, shoreface and inner continental shelf, and define its role in coastal evolution and modern beach behavior; 2) to identify and model the physical processes affecting coastal ocean circulation and sediment transport, and to define their role in shaping the modern shoreline; and 3) to identify sediment sources and transport pathways; leading to construction of a regional sediment budget.