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 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

We projected future streamflow outcomes arising from climate change for the southwestern United States during the 21st century due to climate change under two possible greenhouse gas concentration pathways (RCP4.5 and 8.5). The results inform water managers about the future risks of drought in their water resource regions by providing bounds on the possible locations and extents of streamflow loss. To get to these results, we used downscaled future and historical climate data from seven models to drive a new, calibrated SPAtially Referenced Regression On Watershed attributes (SPARROW) streamflow model (Wise and others, 2019, Miller and others, 2020). Temperature and precipitation data come from the NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30, Thrasher and others, 2013 and Thrasher and others, 2015), and actual and potential evapotranspiration come from the NEX-DCP30 temperature and precipitation used in the Monthly Water Balance Model (MWBM, Hostetler and Alder, 2016 and Alder, 2017a,b,c). This data set comprises climate data preprocessing code to convert the gridded, monthly-scale climate data to reach scale multidecadal averages for the intervals 1975-2005, 2020-2049, 2040-2069 and 2070-2099, the model input (data1) and model control files, the model code, model results files, and code to post-process and analyze the streamflow model results. The raw climate data (NEX-DCP30, MWBM), and SPARROW model calibration documentation are publicly available elsewhere and are cross linked with this data release (see crossref section). The full data preparation, modeling, and analysis methods, as well as results are described in Miller and others, (2021)

This U.S. Geological Survey (USGS) data release includes locations for 12,422 USGS streamgages as indexed along the network of streams (flowlines) in NHDPlus Version 2.1 (NHDPlus v2, Moore and Dewald, 2016). The dataset is one of two datasets developed for the Streamgage Watershed InforMation (SWIM) project. This dataset, which is referred to as “SWIM streamgage locations,” was created in support of the second dataset of basin characteristics and disturbance indexes. The streamgages are located in the conterminous United States and have a minimum record length of 20 years of daily streamflow values or at least 20 years of peak flows (USGS National Water Information System (NWIS) database, U.S. Geological Survey, 2016). This dataset has a total of 13,248 streamgages, 826 of which could not be indexed to NHDPlus v2.1. A custom ArcGIS tool was programmed to conduct linear referencing, which moved each point representing a streamgage to intersect with the nearest flowline and calculated the measure along the segment (expressed as a percentage from its downstream end). The tool then performed a series of automated tests to identify potentially inaccurate locations that were, in turn, individually checked. Comments collected during multiple levels of review were retained in raw form to aid future decisions about the accuracy of the streamgage locations along the medium-resolution (1:100,000-scale) NHDPlus stream segments. The results include the unique flowline identifier (COMID) and measure along the flowline, the reach code and measure along its reach (stream feature that consists of one or more flowlines), review notes, plus the latitude and longitude of the stream-referenced location for each streamgage. This designated position along the NHDPlus network may also be referred to as the hydrographic address of the streamgage. References: Falcone, J.A., 2011, GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow: U.S. Geological Survey dataset, https://doi.org/10.3133/70046617 Moore, R.B., and Dewald, T.G., 2016, The Road to NHDPlus — Advancements in digital stream networks and associated catchments: Journal of the American Water Resources Association, https://doi.org/10.1111/1752-1688.12389 U.S. Geological Survey, 2016, USGS water data for the Nation: U.S. Geological Survey National Water Information System database, accessed October 2016, at https://doi.org/10.5066/F7P55KJN

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 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 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).

The data and R scripts contained in this data release are provided as support for a manuscript titled, "Copula theory as a generalized framework for flow-duration curve based streamflow estimates in ungaged and partially gaged catchments" (Worland and others, 2019) submitted to Water Resources Research. The dv_input.csv contains the measured daily streamflow values for 37 streamgages in the Mobile-Tombigbee River Basin, 4-digit hydrologic unit code (HUC4) 0316, and 37 gages in the Trinity River Basin, HUC4 codes 1201, 1202, 1203, and 1204. The coord_input.csv contains the coordinates and the basin area (squared meters) for the gages in each basin. The R scripts generate daily streamflow estimates using 16 different estimation methods. Additionally, the R scripts also provide a function for estimating leave-one-out cross validated correlations between sites using an ordinary kriging approach. The dv_output.csv files contains the predicted daily streamflow values using the 16 streamflow estimation methods.

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.