Water availability for human and ecosystem needs is a function of both water quantity and water quality, as described in the U.S. Geological Survey (USGS) Water Science Strategy (Evenson and others, 2013). Recently, a quantitative approach to prioritize candidate watersheds for monitoring investment was developed to understand changes in water availability and advance the objectives of new USGS programs (Van Metre and others, 2020). In this study design, the contiguous United States (CONUS) was divided into 18 regions (referred to here as “hydrologic regions” or “HRs”) with relatively homogeneous hydrologic drivers and processes to represent the wide diversity in conditions that exist across the CONUS. The gap analysis focused on prioritizing new capabilities beyond the current USGS science in discharge and constituent concentration trends to develop integrated capabilities for assessing and modeling of the water-quality drivers of aquatic ecosystem health. Water availability can be limited by various water-quality parameters such as temperature, salinity, excess nutrients, suspended sediment, geogenic constituents, and other contaminants of emerging concern (CECs) depending on water sources and human or ecosystem needs (Stanton and others, 2017). This data release contains more than 100 geospatial variables summarized for each watershed at the Hydrologic Unit level 4 (HUC4) that were used to prioritize watersheds targeted for USGS research. Additionally, the data release includes the polygon layers of the modified HUC4 watersheds and the hydrologic regions used for the analyses.

Water availability for human and ecosystem needs is a function of both water quantity and water quality, as described in the U.S. Geological Survey (USGS) Water Science Strategy (Evenson and others, 2013). Recently, a quantitative approach to prioritize candidate watersheds for monitoring investment was developed to understand changes in water availability and advance the objectives of new USGS programs (Van Metre and others, 2020). In this study design, the contiguous United States (CONUS) was divided into 18 regions (referred to here as “hydrologic regions” or “HRs”) with relatively homogeneous hydrologic drivers and processes to represent the wide diversity in conditions that exist across the CONUS. The gap analysis focused on prioritizing new capabilities beyond the current USGS science in discharge and constituent concentration trends to develop integrated capabilities for assessing and modeling of the water-quality drivers of aquatic ecosystem health. Water availability can be limited by various water-quality parameters such as temperature, salinity, excess nutrients, suspended sediment, geogenic constituents, and other contaminants of emerging concern (CECs) depending on water sources and human or ecosystem needs (Stanton and others, 2017). This data release contains more than 100 geospatial variables summarized for each watershed at the Hydrologic Unit level 4 (HUC4) that were used to prioritize watersheds targeted for USGS research. Additionally, the data release includes the polygon layers of the modified HUC4 watersheds and the hydrologic regions used for the analyses.

In 2022, stream reaches at Congaree National Park (CONG) were surveyed following the methods outlined in Monitoring Wadeable Stream Habitat Conditions in Southeast Coast Network Parks (McDonald et al. 2018). On each stream reach, data were collected to provide an understanding of reach- and transect-scale geomorphology and benthic habitat characteristics. In 2021, stream reaches at Chattahoochee River National Recreation Area (CHAT) were surveyed following the same methods (McDonald et al. 2018). In 2019, stream reaches at Horseshoe Bend National Military Park (HOBE), Kennesaw Mountain National Battlefield (KEMO), and Ocmulgee Mounds National Historical Park (OCMU) were surveyed following the same methods (McDonald et al. 2018). In 2018, stream reaches at Congaree National Park (CONG) were surveyed following the same methods (McDonald et al. 2018). In 2017, stream reaches at Chattahoochee River National Recreation Area (CHAT), Kennesaw Mountain National Battlefield (KEMO), and Ocmulgee National Monument (OCMU) were surveyed following the same methods (McDonald et al. 2018). McDonald JM and Others. 2018. Monitoring wadeable stream habitat conditions in Southeast Coast Network parks: Protocol narrative. Natural Resource Report. NPS/SECN/NRR—2018/1715. National Park Service. Fort Collins, Colorado https://irma.nps.gov/DataStore/Reference/Profile/2254874

In 2022, stream reaches at Congaree National Park (CONG) were surveyed following the methods outlined in Monitoring Wadeable Stream Habitat Conditions in Southeast Coast Network Parks (McDonald et al. 2018). On each stream reach, data were collected to provide an understanding of reach- and transect-scale geomorphology and benthic habitat characteristics. In 2021, stream reaches at Chattahoochee River National Recreation Area (CHAT) were surveyed following the same methods (McDonald et al. 2018). In 2019, stream reaches at Horseshoe Bend National Military Park (HOBE), Kennesaw Mountain National Battlefield (KEMO), and Ocmulgee Mounds National Historical Park (OCMU) were surveyed following the same methods (McDonald et al. 2018). In 2018, stream reaches at Congaree National Park (CONG) were surveyed following the same methods (McDonald et al. 2018). In 2017, stream reaches at Chattahoochee River National Recreation Area (CHAT), Kennesaw Mountain National Battlefield (KEMO), and Ocmulgee National Monument (OCMU) were surveyed following the same methods (McDonald et al. 2018). McDonald JM and Others. 2018. Monitoring wadeable stream habitat conditions in Southeast Coast Network parks: Protocol narrative. Natural Resource Report. NPS/SECN/NRR—2018/1715. National Park Service. Fort Collins, Colorado https://irma.nps.gov/DataStore/Reference/Profile/2254874

This data set includes 28 physical watershed attributes for each of 135,118 stream segments (National Hydrodraphy Dataset, Version 1) in California. These data were used to support a report entitled: "Classification of California streams using combined deductive and inductive approaches: setting the foundation for analysis of hydrologic alteration" authored by Pyne, Carlisle, Konrad, and Stein, and published in the journal Ecohydrology. Specifically, these data were used in a classification (ie, cluster) analysis to identify unique groupings of watersheds with similar hydrological characteristics.

This data set includes 28 physical watershed attributes for each of 135,118 stream segments (National Hydrodraphy Dataset, Version 1) in California. These data were used to support a report entitled: "Classification of California streams using combined deductive and inductive approaches: setting the foundation for analysis of hydrologic alteration" authored by Pyne, Carlisle, Konrad, and Stein, and published in the journal Ecohydrology. Specifically, these data were used in a classification (ie, cluster) analysis to identify unique groupings of watersheds with similar hydrological characteristics.

The 4 resource surveys (coastal, rivers and streams, lakes and reservoirs, and wetlands) each have datasets covering the biological, chemical, physical habitat, hydrologic and watershed data. This dataset is associated with the following publication: Kaufmann, P., R.M. Hughes, S. Paulsen, D. Peck, C. Seeliger, T. Kincaid, and R. Mitchell. Physical Habitat in the Conterminous U.S. Streams and Rivers, Part 2: A Quantitative Assessment of Habitat Condition.. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 141: 109047, (2022).

This data set provides the results of a conservation prioritization analysis for wadeable streams in Missouri, USA. Higher values (Maximum of 1) represent higher conservation value. Conservation values were derived using Zonation conservation planning software which used species distribution models, a prioritization algorithm (either Core-Area or Additive Benefit), species weighting (None, Vulnerability, or Listing Status), connecitivity (Yes or No), and masks representing different conservation networks (None, Priority Watersheds, Conservation Opportunity Areas, and Existing Conservation Network). For more information see "An Assessment of Stream Fish Vulnerability and an Evaluation of Conservation Networks in Missouri" by Nicholas Sievert, 2014, University of Missouri-Columbia, Thesis.

This data set provides the results of a conservation prioritization analysis for wadeable streams in Missouri, USA. Higher values (Maximum of 1) represent higher conservation value. Conservation values were derived using Zonation conservation planning software which used species distribution models, a prioritization algorithm (either Core-Area or Additive Benefit), species weighting (None, Vulnerability, or Listing Status), connecitivity (Yes or No), and masks representing different conservation networks (None, Priority Watersheds, Conservation Opportunity Areas, and Existing Conservation Network). For more information see "An Assessment of Stream Fish Vulnerability and an Evaluation of Conservation Networks in Missouri" by Nicholas Sievert, 2014, University of Missouri-Columbia, Thesis.

This dataset contains climate, road salt application, physical, and land cover characteristics summarized for watersheds upstream of 93 USGS stream gages. Data were summarized by watershed using geographic information system software. The dataset consists of one comma-separated variable table.