This dataset represents the density of road and stream crossings 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. The landscape layer (raster) was developed by James Falcone of the USGS. US Census TIGER 2000 line files of roads and the NHDPlusV1 line files of all streams were converted to 30-meter grids where the presence of a street or stream was a 1 and everything else a 0. These were intersected and anything that was a 1 in both grids is the result. The density of road and stream crossings (crossings / square kilometer) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.

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

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

This dataset represents the road density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. This data set is derived from TIGER/Line Files of roads in the conterminous United States. Road density describes how many kilometers of road exist in a square kilometer. A raster was produced using the ArcGIS Line Density Tool to form the landscape layer for analysis. The (kilometer of road/square kilometer) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents the road density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. This data set is derived from TIGER/Line Files of roads in the conterminous United States. Road density describes how many kilometers of road exist in a square kilometer. A raster was produced using the ArcGIS Line Density Tool to form the landscape layer for analysis. The (kilometer of road/square kilometer) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.

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 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 the base flow index values within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. The base-flow index (BFI) grid for the conterminous United States was developed to estimate (1) BFI values for ungaged streams, and (2) ground-water recharge throughout the conterminous United States (see Source_Information). Estimates of BFI values at ungaged streams and BFI-based ground-water recharge estimates are useful for interpreting relations between land use and water quality in surface and ground water. The BFI (%) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents the base flow index values within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. The base-flow index (BFI) grid for the conterminous United States was developed to estimate (1) BFI values for ungaged streams, and (2) ground-water recharge throughout the conterminous United States (see Source_Information). Estimates of BFI values at ungaged streams and BFI-based ground-water recharge estimates are useful for interpreting relations between land use and water quality in surface and ground water. The BFI (%) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents climate observations within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. PRISM is a set of monthly, yearly, and single-event gridded data products of mean temperature and precipitation, max/min temperatures, and dewpoints, primarily for the United States. In-situ point measurements are ingested into the PRISM (Parameter elevation Regression on Independent Slopes Model) statistical mapping system. The PRISM products use a weighted regression scheme to account for complex climate regimes associated with orography, rain shadows, temperature inversions, slope aspect, coastal proximity, and other factors. These data are summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.