This tabular data set represents contact time, the length of time it takes for water to drain along subsurface flow paths to the stream, compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data for contact time was produced by Dave Wolock, (USGS, written communication, 2014) and based on the methods outlined in Wolock and others (1997). Units are days. Contact time is computed from basin topography, soil porosity, and soil hydraulic conductivity. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).

This tabular data set represents contact time, the length of time it takes for water to drain along subsurface flow paths to the stream, compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data for contact time was produced by Dave Wolock, (USGS, written communication, 2014) and based on the methods outlined in Wolock and others (1997). Units are days. Contact time is computed from basin topography, soil porosity, and soil hydraulic conductivity. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).

This tabular data set represents NLCD 2011 percent imperviousness compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data is the "NLCD 2011 Percent Developed Imperviousness (2011 Edition, amended 2014) - National Geospatial Data Asset (NGDA) Land Use Land Cover" which was produced by the United States Geological Survey (Yang and others, 2011). Units are percent. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).

This tabular data set represents NLCD 2011 percent imperviousness compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data is the "NLCD 2011 Percent Developed Imperviousness (2011 Edition, amended 2014) - National Geospatial Data Asset (NGDA) Land Use Land Cover" which was produced by the United States Geological Survey (Yang and others, 2011). Units are percent. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).

This tabular data set represents NLCD 2011 percent imperviousness compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data is the "NLCD 2011 Percent Developed Imperviousness (2011 Edition, amended 2014) - National Geospatial Data Asset (NGDA) Land Use Land Cover" which was produced by the United States Geological Survey (Yang and others, 2011). Units are percent. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).

This tabular data set represents average topgraphic wetness index compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The Topgraphic Wetness Index is a steady state index that’s used to predict areas susceptible to saturated land surfaces and areas that carry the potential to produce overland flow. The index is represented by ln (a/tan(beta)), where ln is the Napierian logarithm, a is the upslope area per unit contour length, and tan/(beta) is the slope gradient (Wolock and McCabe, 1995). The source data for average topgraphic wetness index used here was produced by David Wolock (United States Geological Survey, written communic., 2012). Units are ln(m); where ln(m) = the Naperian logarithm of length, where length is measured in meters. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).

This tabular data set represents average topgraphic wetness index compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The Topgraphic Wetness Index is a steady state index that’s used to predict areas susceptible to saturated land surfaces and areas that carry the potential to produce overland flow. The index is represented by ln (a/tan(beta)), where ln is the Napierian logarithm, a is the upslope area per unit contour length, and tan/(beta) is the slope gradient (Wolock and McCabe, 1995). The source data for average topgraphic wetness index used here was produced by David Wolock (United States Geological Survey, written communic., 2012). Units are ln(m); where ln(m) = the Naperian logarithm of length, where length is measured in meters. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).

This tabular data set represents average topgraphic wetness index compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The Topgraphic Wetness Index is a steady state index that’s used to predict areas susceptible to saturated land surfaces and areas that carry the potential to produce overland flow. The index is represented by ln (a/tan(beta)), where ln is the Napierian logarithm, a is the upslope area per unit contour length, and tan/(beta) is the slope gradient (Wolock and McCabe, 1995). The source data for average topgraphic wetness index used here was produced by David Wolock (United States Geological Survey, written communic., 2012). Units are ln(m); where ln(m) = the Naperian logarithm of length, where length is measured in meters. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).

This tabular data set represents NLCD 2001 percent imperviousness compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data is the "NLCD 2001 Percent Developed Imperviousness (2011 Edition, amended 2014) - National Geospatial Data Asset (NGDA) Land Use Land Cover" which was produced by the United States Geological Survey (Yang and others, 2011). Units are percent. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).

This tabular data set represents NLCD 2001 percent imperviousness compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data is the "NLCD 2001 Percent Developed Imperviousness (2011 Edition, amended 2014) - National Geospatial Data Asset (NGDA) Land Use Land Cover" which was produced by the United States Geological Survey (Yang and others, 2011). Units are percent. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).