This metadata record describes the observed and estimated hydrologic metrics for the 1980 to 2019 period for U.S. Geological Survey streamgage locations across the Conterminous United States. The datasets are arranged in four files: (1) CONUS_Observed_Estimated_HMs_Annual_Monthly.csv, (2) CONUS_Bootstrap_Validations_for_Models.csv, (3) CONUS_Streamflow_Gages_for_Models.csv, and (4) Data_Dictionary_Flow_Metrics.csv. The CONUS_Observed_Estimated_HMs_Annual_Monthly.csv file contains the following six attributes: (1) the U.S. Geological Survey streamgage identification number, (2) calendar year, (3) observed hydrologic metric, (4) estimated hydrologic metric, (5) hydrologic metric abbreviation, and (6) aggregated level 2 ecoregion. The observed hydrologic metrics were calculated using collected streamflow daily values from U.S. Geological Survey streamflow gaging stations (U.S. Geological Survey National Water Information System, http://dx.doi.org/10.5066/F7P55KJN), and the estimated hydrologic metrics were estimated by cross-sectional time series random forest modeling methods by Miller, M.P., Carlisle, D.M., Wolock, D.M., and Wieczorek, M., 2018, A database of natural monthly streamflow estimates from 1950 to 2015 for the conterminous United States: Journal of the American Water Resources Association, 54(6), 1258-1269 [Also available at https://doi.org/10.1111/1752-1688.12685]. Forty-seven hydrologic metrics representing magnitude, frequency, duration, and timing were calculated. The hydrologic metric abbreviations, definitions, units, and citations are detailed in the Data_Dictionary_Flow_Metrics.csv file. The low- and high-flow magnitudes were calculated from the 10th and 90th percentile non-exceedence streamflows divided by the drainage area, respectively. The low- and high-flow frequencies were calculated as the number of pulses below the 10th and above the 90th percentile values, respectively. The low- and high-flow durations were calculated from the length of time (in days) that the streamflow was below the 10th percentile or above the 90th percentile, respectively. The low- and high-flow seasonality values were calculated based on frequency of occurrence in different seasons (for more details, please see Eng, K., Carlisle, D.M., Grantham, T.E., Wolock, D.M., and Eng, R.L., 2019, Severity and extent of alterations to natural streamflow regimes based on hydrologic metrics in the conterminous United States, 1980-2014: U.S. Geological Survey Scientific Investigations Report 2019-5001, 25 p. [Also available at https://doi.org/10.3133/sir20195001]. The CONUS_Streamflow_Gages_for_Models.csv file contains the U.S. Geological Survey list of streamflow gaging stations used in cross-sectional time series random forest models. The CONUS_Bootstrap_Validations_for_Models.csv file lists the U.S. Geological Survey streamflow gaging stations used in the bootstrapped validation data sets used to assess model performance. In addition, bootstrap validation also assesses model robustness by testing various calibration configurations. These bootstrap validation data sets may contain random amounts of observations that are outside the range of the observations used in the calibration, and/or observations that are not independent from one another. There are no missing values in any of the files. The three data files are in a comma separated value text format.

This data release contains trend results computed on the basis of modeled and observed daily streamflows at 502 reference gages across the conterminous U.S. from October 1, 1983 through September 30, 2016. Modeled daily streamflows were computed using the deterministic Precipitation Runoff Modeling System (PRMS), and five statistical techniques: Nearest-Neighbor Drainage Area Ratio (NNDAR), Map-Correlation Drainage Area Ratio (MCDAR), Ordinary Kriging of the logarithms of discharge per unit area (OKDAR), Nearest-Neighbor nonlinear spatial interpolation using flow duration curves (NNQPPQ), and Map-Correlation nonlinear spatial interpolation using flow duration curves (MCQPPQ). Observed daily streamflow data for the study gages were retrieved from the National Water Information System (NWIS). Study gages were selected from among Hydro-Climatic Data Network 2009 (HCDN-2009) gages in the GAGES-II dataset considered to be minimally affected by regulation, diversion, mining, or other anthropogenic activities. Results include trends in annual and monthly means, annual percentiles (1, 5, 10, 25, 50, 75, 90, 95, 99), annual 1-day high, 3-day high, and 7-day low, and annual snowmelt-related runoff timing for a subset of snowmelt dominated basins. Bias and volumetric efficiency statistics between observed and modeled streamflows also are provided.

This data release contains trend results computed on the basis of modeled and observed daily streamflows at 502 reference gages across the conterminous U.S. from October 1, 1983 through September 30, 2016. Modeled daily streamflows were computed using the deterministic Precipitation Runoff Modeling System (PRMS), and five statistical techniques: Nearest-Neighbor Drainage Area Ratio (NNDAR), Map-Correlation Drainage Area Ratio (MCDAR), Ordinary Kriging of the logarithms of discharge per unit area (OKDAR), Nearest-Neighbor nonlinear spatial interpolation using flow duration curves (NNQPPQ), and Map-Correlation nonlinear spatial interpolation using flow duration curves (MCQPPQ). Observed daily streamflow data for the study gages were retrieved from the National Water Information System (NWIS). Study gages were selected from among Hydro-Climatic Data Network 2009 (HCDN-2009) gages in the GAGES-II dataset considered to be minimally affected by regulation, diversion, mining, or other anthropogenic activities. Results include trends in annual and monthly means, annual percentiles (1, 5, 10, 25, 50, 75, 90, 95, 99), annual 1-day high, 3-day high, and 7-day low, and annual snowmelt-related runoff timing for a subset of snowmelt dominated basins. Bias and volumetric efficiency statistics between observed and modeled streamflows also are provided.

This metadata record documents two comma separated text files of average daily fresh-water withdrawal amounts by NHDPlus v2.1 catchment (COMID) within the conterminous United States for calendar year 2010. County-level reported estimated use of water are specifically reported as groundwater and surface water and are allotted to catchments by a sum of the catchment based on evenly distributing the county total across the number of county land-area pixels. All values are reported as gallons per day. Source county-level data were acquired from Estimated use of water in the United States in 2010 (Maupin and others, 2014; available at https://dx.doi.org/10.3133/cir1405). These datasets can be linked to the NHDPlus version 2.1 data suite by the unique identifier COMID (or comid).

This metadata record documents two comma separated text files of average daily fresh-water withdrawal amounts by NHDPlus v2.1 catchment (COMID) within the conterminous United States for calendar year 2010. County-level reported estimated use of water are specifically reported as groundwater and surface water and are allotted to catchments by a sum of the catchment based on evenly distributing the county total across the number of county land-area pixels. All values are reported as gallons per day. Source county-level data were acquired from Estimated use of water in the United States in 2010 (Maupin and others, 2014; available at https://dx.doi.org/10.3133/cir1405). These datasets can be linked to the NHDPlus version 2.1 data suite by the unique identifier COMID (or comid).

This metadata record documents two comma separated text files of average daily fresh-water withdrawal amounts by NHDPlus v2.1 catchment (COMID) within the conterminous United States for calendar year 2010. County-level reported estimated use of water are specifically reported as groundwater and surface water and are allotted to catchments by a sum of the catchment based on evenly distributing the county total across the number of county land-area pixels. All values are reported as gallons per day. Source county-level data were acquired from Estimated use of water in the United States in 2010 (Maupin and others, 2014; available at https://dx.doi.org/10.3133/cir1405). These datasets can be linked to the NHDPlus version 2.1 data suite by the unique identifier COMID (or comid).

This tabular data set represents estimated 30-year (1971-2000) average annual runoff in millimeters per year 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 was compiled by the United States Geological Survey (USGS, Dave Wolock written commun., 2012) based on based on flow measured at streamgages as described in Brakebill and others (2011). Units are millimeters per year. 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 estimated 30-year (1971-2000) average annual runoff in millimeters per year 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 was compiled by the United States Geological Survey (USGS, Dave Wolock written commun., 2012) based on based on flow measured at streamgages as described in Brakebill and others (2011). Units are millimeters per year. 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).

These tabular data sets represent mean 30 year (1971-2000) monthly precipitation (millimeters) data from 800 meter resolution PRISM for two spatial components of the NHDPlus version 2.1 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 mean monthly precipitation from 800 meter resolution resolution PRISM data was produced by the PRISM Group at Oregon State University. Units are millimeters. 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).

These tabular data sets represent mean 30 year (1971-2000) monthly precipitation (millimeters) data from 800 meter resolution PRISM for two spatial components of the NHDPlus version 2.1 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 mean monthly precipitation from 800 meter resolution resolution PRISM data was produced by the PRISM Group at Oregon State University. Units are millimeters. 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).