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

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

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).