This dataset represents total fresh surface-water withdrawals in agricultural land within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Measured as L/day as described in DOI: 10.1016/j.scitotenv.2020.137661

This dataset represents % of land with agricultural drainage, described in DOI: 10.1016/j.scitotenv.2020.137661, within individual, local NHDPlusV2 catchments and upstream, contributing watersheds.

This dataset represents % of land without agricultural drainage, described in DOI: 10.1016/j.scitotenv.2020.137661, within individual, local NHDPlusV2 catchments and upstream, contributing watersheds.

This dataset represents water input, measured as km2/cm: Ratio of the total area of irrigated land to precipitation within individual, local NHDPlusV2 catchments and upstream, contributing watersheds.

This dataset represents the estimated surface water runoff within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and then accumulated to provide watershed-level metrics.(see Data Sources for links to NHDPlusV2 data and metadata) The landscape layer (raster) was developed with a water-balance model developed by Dave Wolock of the USGS and is detailed further in the paper "Independent effects of temperature and precipitation on modeled runoff in the conterminous United States". McCabe and Wolock[2011] Runoff is defined as the flow per unit area delivered to streams and rivers in units of millimeters per month. The runoff estimates were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents estimated surface water TN load within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Measured as kg Nitrogen.

This dataset represents estimated surface water TN flux within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Measured as kg N/km2.

This dataset represents percent area consisting of carbonate-rock aquifers, igneous and metamorphic-rock, sandstone, sandstone and carbonate-rock, semiconsolidated sand, and unconsolidated sand and gravel aquifers within individual, local NHDPlusV2 catchments and upstream, contributing watersheds.

This dataset consists of predicted probabilities of good biological condition based in the US EPA 2008/2009 National Rivers and Streams Assessment (NRSA). NRSA assesses the biological condition of rivers and streams using several approaches, including a benthic invertebrate multimetric index (BMMI). The development of the NRSA BMMI is documented in the 2008/2009 NRSA Report (https://www.epa.gov/national-aquatic-resource-surveys/national-rivers-and-streams-assessment-2008-2009-results) and by Stoddard et al. (2008) (http://www.bioone.org/doi/abs/10.1899/08-053.1). This assessment resulted in the classification of 1,380 streams as being in good or poor biological condition. These sites were paired with StreamCat data and a random forest model was developed to predict the probable condition of streams based on the binary response of condition to catchment and watershed features. This model was then applied to NHDPlusV2 stream segments that were within the NRSA sampling frame, i.e., streams that were candidates for sampling during the 2008/2009 NRSA (~1.1 million stream segments). Model development was documented in Fox et al. (2017) (https://link.springer.com/article/10.1007/s10661-017-6025-0) and Hill et al. (2017)(http://onlinelibrary.wiley.com/doi/10.1002/eap.1617/full).

This dataset represents the dam density and storage volumes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on National Inventory of Dams (NID) data. Attributes were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics.(See Supplementary Info for Glossary of Terms). The NID database contains information about the dams location, size, purpose, type, last inspection, regulatory facts, and other technical data. Structures on streams reduce the longitudinal and lateral hydrologic connectivity of the system. For example, impoundments above dams slow stream flow, cause deposition of sediment and reduce peak flows. Dams change both the discharge and sediment supply of streams, causing channel incision and bed coarsening downstream. Downstream areas are often sediment deprived, resulting in degradation, i.e., erosion of the stream bed and stream banks. This database was improved upon by locations verified by work from the USGS National Map (Jeff Simley Group). It was observed that some dams, some of them major and which do exist, were not part of the 2009 NID, but were represented in the USGS National Map dataset, and had been in the 2006 NID. Approximately 1,100 such dams were added, based on the USGS National Map lat/long and the 2006 NID attributes (dam height, storage, etc.) Finally, as clean-up, a) about 600 records with duplicate NIDID were removed, and b) about 300 records were removed which represented the same location of the same dam but with a different NIDID, for the largest dams (did visual check of dams with storage above 5000 acre feet and are likely duplicated - about the 10,000 largest dams) . 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