To provide daily mean streamflow values at ungaged (partial-record) sites within the Yankee Fork Salmon River watershed, the U.S. Geological Survey (USGS), in cooperation with U.S. Bureau of Reclamation, used discharge measurements at three partial-record sites and related those measurements to a nearby USGS real-time streamgage (index site). Daily mean streamflow was estimated by developing a regression relationship between each partial-record site and the index site for water years 2012-2019. These data are intended to provide daily mean streamflow estimates at partial-record sites as part of a larger study (Clark and others, 2021) to estimate sediment loading for each site.

The U.S. Geological Survey (USGS), in cooperation with the Kootenai Tribe of Idaho, used streamflow measurements at 14 partial-record sites and related them to nearby USGS real-time streamgages (index sites) to provide daily mean streamflow values at ungaged (partial-record) sites. Daily mean streamflow was estimated by developing a regression relationship between streamflow at each partial-record site and the index site for the period of record of the index site. The daily mean streamflow at partial-record sites will support the Kootenai Tribe of Idaho effort to understand fish and wildlife habitat in the watershed and provide streamflow estimates for Kootenai River tributaries for use in hydraulic modeling that supports habitat restoration projects.

The U.S. Geological Survey (USGS), in cooperation with the Kootenai Tribe of Idaho, used streamflow measurements at 14 partial-record sites and related them to nearby USGS real-time streamgages (index sites) to provide daily mean streamflow values at ungaged (partial-record) sites. Daily mean streamflow was estimated by developing a regression relationship between streamflow at each partial-record site and the index site for the period of record of the index site. The daily mean streamflow at partial-record sites will support the Kootenai Tribe of Idaho effort to understand fish and wildlife habitat in the watershed and provide streamflow estimates for Kootenai River tributaries for use in hydraulic modeling that supports habitat restoration projects.

The U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management, used streamflow measurements at 11 partial-record sites and related them to nearby USGS or Idaho Power Company real-time streamgages (index sites) to provide daily mean streamflow values at ungaged (partial-record) sites within the Wild and Scenic River of the Owyhee Canyonlands Wilderness, Idaho. Daily mean streamflow was estimated by developing a regression relationship between streamflow at each partial-record site and the index site for the period of record of the index site. The regressions are then used to estimate annual and semimonthly 20-, 50-, and 80-percent exceedance probability streamflow statistics at each partial-record site. The streamflow statistics will support the Bureau of Land Management’s effort to develop and file a federal water rights claim for sustaining outstanding remarkable values for rivers designated as “Wild,” “Scenic,” or “Recreational”.

The U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management, used streamflow measurements at 11 partial-record sites and related them to nearby USGS or Idaho Power Company real-time streamgages (index sites) to provide daily mean streamflow values at ungaged (partial-record) sites within the Wild and Scenic River of the Owyhee Canyonlands Wilderness, Idaho. Daily mean streamflow was estimated by developing a regression relationship between streamflow at each partial-record site and the index site for the period of record of the index site. The regressions are then used to estimate annual and semimonthly 20-, 50-, and 80-percent exceedance probability streamflow statistics at each partial-record site. The streamflow statistics will support the Bureau of Land Management’s effort to develop and file a federal water rights claim for sustaining outstanding remarkable values for rivers designated as “Wild,” “Scenic,” or “Recreational”.

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)

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)

The continental United States (CONUS) was modeled to produce simulations of historical and potential future streamflow using the Precipitation-Runoff Modeling System (PRMS) application of the USGS National Hydrologic Model infrastructure (NHM; Regan and others, 2018). This child page specifically contains a suite of 52 streamflow metrics. These metrics were computed using daily outputs of runoff from HRUs (PRMS variable hru_outflow) and streamflow from the model stream segments (PRMS variable seg_outflow) for all historical and future simulations (table1_GCMs_used.csv) with both static and dynamic land cover parameters. These streamflow statistics describe the duration, frequency, magnitude, rate of change, and timing of streamflow computed for historical and future simulation periods (streamflow_statistics_description_table.csv).

The continental United States (CONUS) was modeled to produce simulations of historical and potential future streamflow using the Precipitation-Runoff Modeling System (PRMS) application of the USGS National Hydrologic Model infrastructure (NHM; Regan and others, 2018). This child page specifically contains a suite of 52 streamflow metrics. These metrics were computed using daily outputs of runoff from HRUs (PRMS variable hru_outflow) and streamflow from the model stream segments (PRMS variable seg_outflow) for all historical and future simulations (table1_GCMs_used.csv) with both static and dynamic land cover parameters. These streamflow statistics describe the duration, frequency, magnitude, rate of change, and timing of streamflow computed for historical and future simulation periods (streamflow_statistics_description_table.csv).

This data release contains the input and output used to assess the potential effect of climate on streamflow and salinity (measured as total dissolved solids [TDS]) yields across the Upper Colorado River Basin from water years 1986 to 2021. This analysis included estimation of the spatiotemporal variability in mean annual climatic variables (air temperature, snow water equivalent, precipitation and antecedent precipitation), mean annual streamflow yields, and mean annual TDS yields at 34 sites within the basin. Generalized Additive Models (GAMs) were used to look at non-linear trends in streamflow and TDS yields in the Upper Colorado River Basin. GAMs were also used to create attribution models that explain temporal variability in streamflow and TDS using climate variables (precipitation, snow, and air temperature). A detailed description of the analysis is provided in the associated journal article.