This data release contains 29 streamflow statistics computed from modeled and observed daily streamflows from October 1, 1983, through September 30, 2016 at 1,114 streamgages in 19 study regions covering the conterminous United States. The streamflow statistics were computed at selected GAGES-II reference streamgages (Falcone, 2011) from daily streamflow observations (Russell and others, 2020), from daily streamflow time series computed using the National Hydrologic Model-Precipitation Runoff Modeling System (NHM-PRMS) model (“by headwater” and “by observation” calibrations with Muskingum routing; Hay and LaFontaine, 2020), from daily streamflow time series computed using five statistical time series models (Russell and others, 2020), and from three direct statistical prediction methods (Over and others, unpub. data, 2020). The data release comprises twelve .csv files. The streamflow statistics values are provided in eleven of these files, one each for the observed, the two NHM-PRMS calibrations, the five statistical time series models, and the three direct statistical prediction methods. The remaining file is a summary table, which provides period-of-record information for each streamgage. References cited: Falcone, J.A., 2011, GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow [digital spatial dataset] : U.S. Geological Survey Water Resources NSDI Node web page, https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011. Hay, L.E., and LaFontaine, J.H., 2020, Application of the National Hydrologic Model Infrastructure with the Precipitation-Runoff Modeling System (NHM-PRMS),1980-2016, Daymet Version 3 calibration: U.S. Geological Survey data release, https://doi.org/10.5066/P9PGZE0S Russell, A.M., Over, T.M., and Farmer, W.H., 2020, Cross-validation results for five statistical methods of daily streamflow estimation at 1,385 reference streamgages in the conterminous United States, Water Years 1981-2017: U.S. Geological Survey data release, https://doi.org/10.5066/P9XT4WSP

This data release contains values of 29 streamflow statistics computed from modeled and observed daily streamflows from October 1, 1983, through September 30, 2016 at 1,257 streamgages in the 19 study regions defined by Falcone (2011) covering the conterminous United States. The streamflow statistics were computed at GAGES-II non-reference streamgages (Falcone, 2011), determined to be affected by only irrigation or regulation among antrhopogenic influences. At each streamgage, statistics were computed from daily streamflow observations, from daily streamflow time series computed using the National Hydrologic Model-Precipitation Runoff Modeling System (NHM-PRMS) model (the “by headwater” and "by observation" calibrations with Muskingum routing; Hay and LaFontaine, 2020), and from daily streamflow time series computed using five statistical time series models fitted to reference basins (Russell and others, 2021). The data release comprises nine .csv files. The streamflow statistics values are provided in eight of these files, one each for the observed, the two NHM-PRMS calibrations, and the five statistical time series models. The remaining file is a summary table, which provides period-of-record information for each streamgage. References cited: Falcone, J.A., 2011, GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow [digital spatial dataset]: U.S. Geological Survey Water Resources NSDI Node web page, https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011. Hay, L.E., and LaFontaine, J.H., 2020, Application of the National Hydrologic Model Infrastructure with the Precipitation-Runoff Modeling System (NHM-PRMS), 1980-2016, Daymet Version 3 calibration: U.S. Geological Survey data release, https://doi.org/10.5066/P9PGZE0S. Russell, A.M., Over, T.M., Farmer, W.H., and Miles, K.J., 2021, Statistical daily streamflow estimates at GAGES-II non-reference streamgages in the conterminous Unites States, Water Years 1981-2017: U.S. Geological Survey data release, https://doi.org/10.5066/P9PA9PKM.

This data release contains daily time series estimates of natural streamflow at 5,439 GAGES-II non-reference streamgages in 19 study regions across the conterminous United States from October 1, 1980 through September 30, 2017, using five statistical techniques: nearest-neighbor drainage area ratio (NNDAR), map-correlation drainage area ratio (MCDAR), nearest-neighbor nonlinear spatial interpolation using flow duration curves (NNQPPQ), map-correlation nonlinear spatial interpolation using flow duration curves (MCQPPQ), and ordinary kriging of the logarithms of discharge per unit area (OKDAR). NNDAR, MCDAR, NNQPPQ, and MCQPPQ estimates were computed following methods described in Farmer and others (2014), with updates to the flow-duration curve modeling which is described in Over and others (2018). OKDAR estimates were computed using pooled variograms for each study region following methods described in Farmer (2016). Daily streamflow estimation was conducted by study region (hydrologic unit code level-2 regions as defined in Falcone, 2011) by building statistical models using 1,385 GAGES-II reference streamgages from mostly undisturbed watersheds as index gages (Russell and others, 2020). Estimates were then made at GAGES-II non-reference streamgages. Location information and basin characteristics for study gages were obtained from the GAGES-II dataset (Falcone, 2011). Observed daily streamflow data were retrieved from the National Water Information System (USGS, 2019). This data release contains 19 separate zip files; one for each study region. Each zip file contains an individual tab-delimited text file for each non-reference streamgage in the study region. A text file summarizing period of record information for each non-reference streamgage is provided (non-reference_gages_summary.csv). This data release also contains a text file (Model_info.csv) of regional regression equations for 27 flow quantiles that were developed in each study region in order to implement the QPPQ methods and a text file (BC_transformations.csv) describing transformations made to the GAGES-II derived basin characteristics prior to use in the regression equations. The five sets of streamflow estimates represent expected natural streamflow conditions with minimal disturbance by human activities, in other words, without the effects of regulation, diversion, land development, or other anthropogenic activities. The observed streamflow records at the non-reference streamgages were compared to the five simulated streamflow records. These performance metrics are provided at each gage for all five statistical methods (NonRef_PMs_byStation.csv) and as summaries by region (NonRef_PM_summaries_byRegion.csv). References cited: Falcone, J.A., 2011, GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow [digital spatial dataset]: U.S. Geological Survey Water Resources NSDI Node web page, https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011. Farmer, W.H., Archfield, S.A., Over, T.M., Hay, L.E., LaFontaine, J.H., and Kiang, J.E., 2014, A comparison of methods to predict historical daily streamflow time series in the southeastern United States: U.S. Geological Survey Scientific Investigations Report 2014–5231, 34 p., http://dx.doi.org/10.3133/sir20145231. Farmer, W. H., 2016, Ordinary kriging as a tool to estimate historical daily streamflow records, Hydrology and Earth System Sciences, 20, 2721-2735, https://doi.org/10.5194/hess-20-2721-2016. Over, T.M., Farmer, W.H., and Russell, A.M., 2018, Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States: U.S. Geological Survey Scientific Investigations Report 2018–5072, 34 p., https://doi.org/10.3133/sir20185072. Russell, A.M., Over, T.M., and Farmer, W.H., 2020, Cross-validation results for five statistical methods of daily streamflow estimation at 1,385 reference streamgages in the conterminous United States, Water Years

This data release contains daily time series estimates of natural streamflow at 5,439 GAGES-II non-reference streamgages in 19 study regions across the conterminous United States from October 1, 1980 through September 30, 2017, using five statistical techniques: nearest-neighbor drainage area ratio (NNDAR), map-correlation drainage area ratio (MCDAR), nearest-neighbor nonlinear spatial interpolation using flow duration curves (NNQPPQ), map-correlation nonlinear spatial interpolation using flow duration curves (MCQPPQ), and ordinary kriging of the logarithms of discharge per unit area (OKDAR). NNDAR, MCDAR, NNQPPQ, and MCQPPQ estimates were computed following methods described in Farmer and others (2014), with updates to the flow-duration curve modeling which is described in Over and others (2018). OKDAR estimates were computed using pooled variograms for each study region following methods described in Farmer (2016). Daily streamflow estimation was conducted by study region (hydrologic unit code level-2 regions as defined in Falcone, 2011) by building statistical models using 1,385 GAGES-II reference streamgages from mostly undisturbed watersheds as index gages (Russell and others, 2020). Estimates were then made at GAGES-II non-reference streamgages. Location information and basin characteristics for study gages were obtained from the GAGES-II dataset (Falcone, 2011). Observed daily streamflow data were retrieved from the National Water Information System (USGS, 2019). This data release contains 19 separate zip files; one for each study region. Each zip file contains an individual tab-delimited text file for each non-reference streamgage in the study region. A text file summarizing period of record information for each non-reference streamgage is provided (non-reference_gages_summary.csv). This data release also contains a text file (Model_info.csv) of regional regression equations for 27 flow quantiles that were developed in each study region in order to implement the QPPQ methods and a text file (BC_transformations.csv) describing transformations made to the GAGES-II derived basin characteristics prior to use in the regression equations. The five sets of streamflow estimates represent expected natural streamflow conditions with minimal disturbance by human activities, in other words, without the effects of regulation, diversion, land development, or other anthropogenic activities. The observed streamflow records at the non-reference streamgages were compared to the five simulated streamflow records. These performance metrics are provided at each gage for all five statistical methods (NonRef_PMs_byStation.csv) and as summaries by region (NonRef_PM_summaries_byRegion.csv). References cited: Falcone, J.A., 2011, GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow [digital spatial dataset]: U.S. Geological Survey Water Resources NSDI Node web page, https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011. Farmer, W.H., Archfield, S.A., Over, T.M., Hay, L.E., LaFontaine, J.H., and Kiang, J.E., 2014, A comparison of methods to predict historical daily streamflow time series in the southeastern United States: U.S. Geological Survey Scientific Investigations Report 2014–5231, 34 p., http://dx.doi.org/10.3133/sir20145231. Farmer, W. H., 2016, Ordinary kriging as a tool to estimate historical daily streamflow records, Hydrology and Earth System Sciences, 20, 2721-2735, https://doi.org/10.5194/hess-20-2721-2016. Over, T.M., Farmer, W.H., and Russell, A.M., 2018, Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States: U.S. Geological Survey Scientific Investigations Report 2018–5072, 34 p., https://doi.org/10.3133/sir20185072. Russell, A.M., Over, T.M., and Farmer, W.H., 2020, Cross-validation results for five statistical methods of daily streamflow estimation at 1,385 reference streamgages in the conterminous United States, Water Years

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 data release contains daily time series estimates of natural streamflow for 1,385 streamgages in 19 study regions in the conterminous U.S. from October 1, 1980, through September 30, 2017. These estimates are provided for gages from mostly undisturbed watersheds as defined by Falcone (2011), using five statistical techniques: nearest-neighbor drainage area ratio (NNDAR), map-correlation drainage area ratio (MCDAR), nearest-neighbor nonlinear spatial interpolation using flow duration curves (NNQPPQ), map-correlation nonlinear spatial interpolation using flow duration curves (MCQPPQ), and ordinary kriging of the logarithms of discharge per unit area (OKDAR). Location information and basin characteristics for study gages were obtained from the "Reference" gages of the GAGES-II dataset (Falcone, 2011, https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011). Observed daily streamflow data were retrieved from the National Water Information System (NWIS) on September 7, 2018. NNDAR, MCDAR, NNQPPQ, and MCQPPQ estimates were computed following methods described by Farmer and others (2014), with updates to the flow-duration curve modeling which is described by Over and others (2018). OKDAR estimates were computed using pooled variograms for each study region following methods described by Farmer (2016). Daily streamflow estimation was conducted in a leave-one-out-cross-validation approach where each streamgage was treated as if ungaged and all the remaining streamgages in a study region were used to calibrate each method and perform estimations at the "ungaged" site. The observed streamflow records were compared to the five simulated streamflow records to help assess performance of each method. These performance metrics are provided at each gage for all five statistical methods. References cited: Falcone, J.A., 2011, GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow [digital spatial dataset] : U.S. Geological Survey Water Resources NSDI Node web page, https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011. Farmer, W.H., Archfield, S.A., Over, T.M., Hay, L.E., LaFontaine, J.H., and Kiang, J.E., 2014, A comparison of methods to predict historical daily streamflow time series in the southeastern United States: U.S. Geological Survey Scientific Investigations Report 2014–5231, 34 p., http://dx.doi.org/10.3133/sir20145231. Farmer, W. H., 2016, Ordinary kriging as a tool to estimate historical daily streamflow records, Hydrology and Earth System Sciences, 20, 2721-2735, https://doi.org/10.5194/hess-20-2721-2016. Over, T.M., Farmer, W.H., Russell, A.M., 2018, Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States; U.S. Geological Survey Scientific Investigations Report 2018–5072, https://doi.org/10.3133/sir20185072.

This data release contains daily time series estimates of natural streamflow for 1,385 streamgages in 19 study regions in the conterminous U.S. from October 1, 1980, through September 30, 2017. These estimates are provided for gages from mostly undisturbed watersheds as defined by Falcone (2011), using five statistical techniques: nearest-neighbor drainage area ratio (NNDAR), map-correlation drainage area ratio (MCDAR), nearest-neighbor nonlinear spatial interpolation using flow duration curves (NNQPPQ), map-correlation nonlinear spatial interpolation using flow duration curves (MCQPPQ), and ordinary kriging of the logarithms of discharge per unit area (OKDAR). Location information and basin characteristics for study gages were obtained from the "Reference" gages of the GAGES-II dataset (Falcone, 2011, https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011). Observed daily streamflow data were retrieved from the National Water Information System (NWIS) on September 7, 2018. NNDAR, MCDAR, NNQPPQ, and MCQPPQ estimates were computed following methods described by Farmer and others (2014), with updates to the flow-duration curve modeling which is described by Over and others (2018). OKDAR estimates were computed using pooled variograms for each study region following methods described by Farmer (2016). Daily streamflow estimation was conducted in a leave-one-out-cross-validation approach where each streamgage was treated as if ungaged and all the remaining streamgages in a study region were used to calibrate each method and perform estimations at the "ungaged" site. The observed streamflow records were compared to the five simulated streamflow records to help assess performance of each method. These performance metrics are provided at each gage for all five statistical methods. References cited: Falcone, J.A., 2011, GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow [digital spatial dataset] : U.S. Geological Survey Water Resources NSDI Node web page, https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011. Farmer, W.H., Archfield, S.A., Over, T.M., Hay, L.E., LaFontaine, J.H., and Kiang, J.E., 2014, A comparison of methods to predict historical daily streamflow time series in the southeastern United States: U.S. Geological Survey Scientific Investigations Report 2014–5231, 34 p., http://dx.doi.org/10.3133/sir20145231. Farmer, W. H., 2016, Ordinary kriging as a tool to estimate historical daily streamflow records, Hydrology and Earth System Sciences, 20, 2721-2735, https://doi.org/10.5194/hess-20-2721-2016. Over, T.M., Farmer, W.H., Russell, A.M., 2018, Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States; U.S. Geological Survey Scientific Investigations Report 2018–5072, https://doi.org/10.3133/sir20185072.

This dataset contains the empirical flow-duration curves (FDCs) derived from complete water years of daily streamflow data for 1,378 streamgages in 19 study regions in the conterminous U.S. from October 1, 1980 through September 30, 2013 from mostly undisturbed watersheds contained in child item 1, "Daily streamflow data for selected streamgages in the conterminous United States", of this data release. The empirical FDCs are presented as 27 quantiles ranging from 0.02 to 99.98 percent nonexceedance probabilities. Because streamflow data less than 0.005 cfs are reported as zero, they are considered to be censored values. To handle these censored data values, two versions of the FDC quantiles from streamgage records were computed: (1) empFDCs.unfilled.xlsx - where the quantiles were estimated from the original data and (2) empFDCs.filled.xlsx – where the censored quantile values were filled with estimated positive values. With the method used for filling the censored quantiles, which relies on a lognormal fit to the data, occasionally the data values estimated for the largest censored values were larger than the smallest noncensored data values. This sometimes resulted in increases to the quantiles greater than the censoring level. As a result, some of the noncensored flow quantile values in the filled dataset are greater than the corresponding noncensored flow quantile values in the unfilled dataset. Methods are fully described by Over and others (2018).

This dataset contains the empirical flow-duration curves (FDCs) derived from complete water years of daily streamflow data for 1,378 streamgages in 19 study regions in the conterminous U.S. from October 1, 1980 through September 30, 2013 from mostly undisturbed watersheds contained in child item 1, "Daily streamflow data for selected streamgages in the conterminous United States", of this data release. The empirical FDCs are presented as 27 quantiles ranging from 0.02 to 99.98 percent nonexceedance probabilities. Because streamflow data less than 0.005 cfs are reported as zero, they are considered to be censored values. To handle these censored data values, two versions of the FDC quantiles from streamgage records were computed: (1) empFDCs.unfilled.xlsx - where the quantiles were estimated from the original data and (2) empFDCs.filled.xlsx – where the censored quantile values were filled with estimated positive values. With the method used for filling the censored quantiles, which relies on a lognormal fit to the data, occasionally the data values estimated for the largest censored values were larger than the smallest noncensored data values. This sometimes resulted in increases to the quantiles greater than the censoring level. As a result, some of the noncensored flow quantile values in the filled dataset are greater than the corresponding noncensored flow quantile values in the unfilled dataset. Methods are fully described by Over and others (2018).