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 predicted flow-duration curves (FDCs) for 1,378 streamgages in 19 study regions in the conterminous U.S. from mostly undisturbed watersheds using regression models constructed with four or five binary methodological choices (thus 16 or 32 methodological combinations). The predicted FDCs are presented as 27 quantiles ranging from 0.02 to 99.98 percent nonexceedance probabilities. These data are also contained within the CSV files in child item 4, "Selected regression models for predicting FDC quantiles for selected streamgages in the conterminous United States", but are separated out here to provide more convenient access in a single Excel file (predictedFDCs.xlsx). These data support a concurrent publication (Over and others, 2018).

This dataset contains predicted flow-duration curves (FDCs) for 1,378 streamgages in 19 study regions in the conterminous U.S. from mostly undisturbed watersheds using regression models constructed with four or five binary methodological choices (thus 16 or 32 methodological combinations). The predicted FDCs are presented as 27 quantiles ranging from 0.02 to 99.98 percent nonexceedance probabilities. These data are also contained within the CSV files in child item 4, "Selected regression models for predicting FDC quantiles for selected streamgages in the conterminous United States", but are separated out here to provide more convenient access in a single Excel file (predictedFDCs.xlsx). These data support a concurrent publication (Over and others, 2018).

This data release contains the input used and the output files interpreted in the publication "Refinement of a Regression-Based Method for Prediction of Flow-Duration Curves of Daily Streamflow in the Conterminous United States". This data release contains daily streamflow data for 1,378 streamgages in 19 study regions in the conterminous U.S. (CONUS) from October 1, 1980 through September 30, 2013 from mostly undisturbed watersheds. This data release also contains the empirical flow-duration curves (FDCs) derived from this daily streamflow data, presented as 27 quantiles ranging from 0.02 to 99.98 percent nonexceedance probabilities. Selected basin characteristics from the GAGES-II dataset (https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011) were transformed to reduce skewness and to convert to a similar range of values and then used, directly or in the construction of additional variables, to fit regression equations for predicting FDCs. Basin characteristic selection and transformation was performed separately for each study region. The basin characteristics considered for use in candidate regression models are presented in their original units and as their transformed values; a table specifying the variable transformations is also provided. To each group of gaged basins in each region with one basin left out, a regression model selection procedure, with four or five binary methodological choices thus 16 or 32 methodological combinations, was applied to select the best regression model for each contiguous group of FDC quantiles (called here a “flow regime”). This data release provides the definitions of the selected flow regimes, the regression model parameters, goodness-of-fit statistics of the fitted models, and predicted FDCs for the gaged basin that was left out for the selected FDC regression models for each of the methodological combinations.

This data release contains the input used and the output files interpreted in the publication "Refinement of a Regression-Based Method for Prediction of Flow-Duration Curves of Daily Streamflow in the Conterminous United States". This data release contains daily streamflow data for 1,378 streamgages in 19 study regions in the conterminous U.S. (CONUS) from October 1, 1980 through September 30, 2013 from mostly undisturbed watersheds. This data release also contains the empirical flow-duration curves (FDCs) derived from this daily streamflow data, presented as 27 quantiles ranging from 0.02 to 99.98 percent nonexceedance probabilities. Selected basin characteristics from the GAGES-II dataset (https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011) were transformed to reduce skewness and to convert to a similar range of values and then used, directly or in the construction of additional variables, to fit regression equations for predicting FDCs. Basin characteristic selection and transformation was performed separately for each study region. The basin characteristics considered for use in candidate regression models are presented in their original units and as their transformed values; a table specifying the variable transformations is also provided. To each group of gaged basins in each region with one basin left out, a regression model selection procedure, with four or five binary methodological choices thus 16 or 32 methodological combinations, was applied to select the best regression model for each contiguous group of FDC quantiles (called here a “flow regime”). This data release provides the definitions of the selected flow regimes, the regression model parameters, goodness-of-fit statistics of the fitted models, and predicted FDCs for the gaged basin that was left out for the selected FDC regression models for each of the methodological combinations.

This dataset contains a zipped file (dailyQs.zip) 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. USGS streamgages that were identified as being of “reference” quality in the GAGES-II dataset (https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011) and had at least 10 complete water years (WYs) during the study period from WY1981 through WY2013 were selected. Daily streamflow data were retrieved from the National Water Information System (NWIS) on April 18, 2016. This dataset also contains an Excel file (compWYs.xlsx) indicating for each WY during the study period whether a streamgage had a complete streamflow record (no missing values) during that year. Only complete WYs of daily streamflow data during the study period from the selected streamgages were used to compute the empirical FDC quantiles to which regression equations were fitted. These data support a concurrent publication (Over and others, 2018).

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 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 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 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