High-Resolution Hydrographic Mapping on a portion of the Big Sioux River Basin in Southeast South Dakota, 2016

A High-Resolution Hydrographic Mapping effort was completed for thirteen 12-digit hydrologic units in the Big Sioux River Basin near Sioux Falls in southeastern South Dakota. A digital elevation model based on light detection and ranging (lidar) data was prepared from four sources. Known culverts were hydro-enforced into the elevation model, and selective drainage techniques were utilized within geographic information systems software to identify additional locations where bridges or culverts needed to be hydro-enforced. These potential locations were given a preliminary screening using aerial imagery, and likely locations were further screened using high-resolution oblique aerial imagery or with site visits. Locations with confirmed culverts were also hydro-enforced. The raw and hydro-enforced elevation models were used to generate flow derivative layers. The elevation models, flow derivative layers, and culvert layer are included as geospatial data layers within this data release. This study was completed by the U.S. Geological Survey, Dakota Water Science Center in cooperation with the City of Sioux Falls, the City of Harrisburg, Lincoln County, the South Dakota Department of Transportation, East Dakota Water Development District, and the Mid-America GIS Consortium.

Data and Resources

Field Value
accessLevel public
bureauCode {010:12}
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identifier USGS:5a3ad6cce4b0d05ee8b5ce47
metadata_type geospatial
modified 20200818
old-spatial -97.124675206, 43.356189078, -96.361149558, 43.827459113
publisher U.S. Geological Survey
publisher_hierarchy Department of the Interior > U.S. Geological Survey
resource-type Dataset
source_datajson_identifier true
source_hash e865244f40e32fec0e68ed5c6803a24e11609253
source_schema_version 1.1
spatial {"type": "Polygon", "coordinates": [[[-97.124675206, 43.356189078], [-97.124675206, 43.827459113], [ -96.361149558, 43.827459113], [ -96.361149558, 43.356189078], [-97.124675206, 43.356189078]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • amerigeo
  • amerigeoss
  • ckan
  • culvert-hydro-enforcement
  • drainage-basins
  • geo
  • geoss
  • inlandwaters
  • lidar
  • lincoln-county
  • minnehaha-county
  • national
  • north-america
  • sioux-falls
  • south-dakota
  • united-states
  • usgs-5a3ad6cce4b0d05ee8b5ce47
isopen False
license_id notspecified
license_title License not specified
maintainer Ryan F Thompson
maintainer_email rcthomps@usgs.gov
metadata_created 2025-11-21T11:27:14.778884
metadata_modified 2025-11-21T11:27:14.778888
notes A High-Resolution Hydrographic Mapping effort was completed for thirteen 12-digit hydrologic units in the Big Sioux River Basin near Sioux Falls in southeastern South Dakota. A digital elevation model based on light detection and ranging (lidar) data was prepared from four sources. Known culverts were hydro-enforced into the elevation model, and selective drainage techniques were utilized within geographic information systems software to identify additional locations where bridges or culverts needed to be hydro-enforced. These potential locations were given a preliminary screening using aerial imagery, and likely locations were further screened using high-resolution oblique aerial imagery or with site visits. Locations with confirmed culverts were also hydro-enforced. The raw and hydro-enforced elevation models were used to generate flow derivative layers. The elevation models, flow derivative layers, and culvert layer are included as geospatial data layers within this data release. This study was completed by the U.S. Geological Survey, Dakota Water Science Center in cooperation with the City of Sioux Falls, the City of Harrisburg, Lincoln County, the South Dakota Department of Transportation, East Dakota Water Development District, and the Mid-America GIS Consortium.
num_resources 2
num_tags 17
title High-Resolution Hydrographic Mapping on a portion of the Big Sioux River Basin in Southeast South Dakota, 2016