The StreamCat Dataset provides summaries of natural and anthropogenic landscape features for ~2.65 million streams, and their associated catchments, within the conterminous USA. This dataset is associated with the following publication: Hill, R.A., M. Weber , S. Leibowitz , T. Olsen , and D.J. Thornbrugh. The Stream-Catchment (StreamCat) Dataset: A database of watershed metrics for the conterminous USA. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, USA, 9, (2015).

The StreamCat Dataset provides summaries of natural and anthropogenic landscape features for ~2.65 million streams, and their associated catchments, within the conterminous USA. This dataset is associated with the following publications: Hill, R.A., M. Weber , S. Leibowitz , T. Olsen , and D.J. Thornbrugh. The Stream-Catchment (StreamCat) Dataset: A database of watershed metrics for the conterminous USA. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, USA, 9, (2015). Hill, R., E. Fox, S. Leibowitz, T. Olsen, D. Thornbrugh, and M. Weber. Predictive Mapping of the Biotic Condition of Conterminous-USA Rivers and Streams. ECOLOGICAL APPLICATIONS. Ecological Society of America, Ithaca, NY, USA, 27(8): 2397-2415, (2017). Fox, E., R. Hill, S. Leibowitz, T. Olsen, D. Thornbrugh, and M. Weber. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 189(316): 1-20, (2017). Thornbrugh, D., S. Leibowitz, R. Hill, M. Weber, Z. Johnson, T. Olsen, J. Flotemersch, J. Stoddard, and D. Peck. Mapping watershed integrity for the conterminous United States... ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 85: 1133-1148, (2018).

The StreamCat Dataset provides summaries of natural and anthropogenic landscape features for ~2.65 million streams, and their associated catchments, within the conterminous USA. This dataset is associated with the following publications: Hill, R.A., M. Weber , S. Leibowitz , T. Olsen , and D.J. Thornbrugh. The Stream-Catchment (StreamCat) Dataset: A database of watershed metrics for the conterminous USA. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, USA, 9, (2015). Hill, R., E. Fox, S. Leibowitz, T. Olsen, D. Thornbrugh, and M. Weber. Predictive Mapping of the Biotic Condition of Conterminous-USA Rivers and Streams. ECOLOGICAL APPLICATIONS. Ecological Society of America, Ithaca, NY, USA, 27(8): 2397-2415, (2017). Fox, E., R. Hill, S. Leibowitz, T. Olsen, D. Thornbrugh, and M. Weber. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 189(316): 1-20, (2017). Thornbrugh, D., S. Leibowitz, R. Hill, M. Weber, Z. Johnson, T. Olsen, J. Flotemersch, J. Stoddard, and D. Peck. Mapping watershed integrity for the conterminous United States... ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 85: 1133-1148, (2018).

This dataset represents the density of 18 USGS lithology classes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds(see Data Sources for links to NHDPlusV2 data and USGS). Attributes were calculated for every local NHDPlusV2 catchment and then accumulated to provide watershed-level metrics for USGS lithology data. This data set is derived from the USGS raster map of 18 lithology classes (categorical data type) for the conterminous USA. The map was produced based on texture, internal structure, thickness, and environment of deposition or formation of materials. These 18 lithology classes were summarized by local catchment and by watershed to produce 18 local catchment-level and watershed-level metrics as a categorical data type.

This dataset represents the density of 18 USGS lithology classes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds(see Data Sources for links to NHDPlusV2 data and USGS). Attributes were calculated for every local NHDPlusV2 catchment and then accumulated to provide watershed-level metrics for USGS lithology data. This data set is derived from the USGS raster map of 18 lithology classes (categorical data type) for the conterminous USA. The map was produced based on texture, internal structure, thickness, and environment of deposition or formation of materials. These 18 lithology classes were summarized by local catchment and by watershed to produce 18 local catchment-level and watershed-level metrics as a categorical data type.

This dataset represents data derived from the NLCD dataset and the National Hydrography Dataset version 2.1(NHDPlusV2) (see Data Sources for links to NHDPlusV2 data and NLCD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated upstream catchments to provide watershed-level metrics for imperviousness values within the NLCD. This data set is derived from the NLCD Impervious Surfaces raster, which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019 Landsat satellite data. This dataset will include additional years as they become available.

This dataset represents data derived from the NLCD dataset and the National Hydrography Dataset version 2.1(NHDPlusV2) (see Data Sources for links to NHDPlusV2 data and NLCD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated upstream catchments to provide watershed-level metrics for imperviousness values within the NLCD. This data set is derived from the NLCD Impervious Surfaces raster, which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019 Landsat satellite data. This dataset will include additional years as they become available.

This dataset represents the dam density and storage volumes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on the National Anthropogenic Barrier Dataset (NABD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. The main objective of this project was to develop a dataset of large, anthropogenic barriers that are spatially linked to the National Hydrography Dataset Plus Version 1 (NHDPlusV1) for the conterminous U.S. to facilitate GIS analyses based on the NHDPlusV1/NHD and NID datasets. To meet this objective, Michigan State University conducted a spatial linkage of the point dataset of the 2009 National Inventory of Dams (NID) created by the U.S. Army Corps of Engineers (USACE) to the NHDPlusV1/NHD. The pool of dam data included were modified based on 1) dam removals that occurred after development of the 2009 NID and 2) the identification of duplicate dam records along state boundaries (cases where more than one state reported the same dam). The US Geological Survey (USGS) Aquatic GAP Program supported this work. The (dams/catchment) and (dam_storage/catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.

This dataset represents the dam density and storage volumes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on the National Anthropogenic Barrier Dataset (NABD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. The main objective of this project was to develop a dataset of large, anthropogenic barriers that are spatially linked to the National Hydrography Dataset Plus Version 1 (NHDPlusV1) for the conterminous U.S. to facilitate GIS analyses based on the NHDPlusV1/NHD and NID datasets. To meet this objective, Michigan State University conducted a spatial linkage of the point dataset of the 2009 National Inventory of Dams (NID) created by the U.S. Army Corps of Engineers (USACE) to the NHDPlusV1/NHD. The pool of dam data included were modified based on 1) dam removals that occurred after development of the 2009 NID and 2) the identification of duplicate dam records along state boundaries (cases where more than one state reported the same dam). The US Geological Survey (USGS) Aquatic GAP Program supported this work. The (dams/catchment) and (dam_storage/catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.

This dataset represents slope percent along stream within individual, local NHDPlusV2 catchments and upstream, contributing watersheds.