Identifying long-term trends in water availability, including surface water quantity, is a key part of the U.S. Geological Survey (USGS) Integrated Water Availability Assessments (IWAAs) mission. This data release includes input and output data used in Mann-Kendall trend analyses to characterize streamflow conditions at 124 USGS streamgages in the Upper Colorado River Basin for water years 1982 through 2021. The Upper Colorado Riven Basin is defined here as the basin area upstream of USGS streamgage Colorado River above Lee's Ferry, AZ (USGS site number 09380000). Input data included annual (111 streamgages), seasonal (119 streamgages), and monthly (121 streamgages) streamflow metrics, calculated from daily mean streamflow data from the USGS National Water Information System (NWIS) database. Annual streamflow metrics include mean and median annual streamflow, 1-day, 7-day, and 30-day maximum annual streamflow; 1-day, 7-day, and 30-day minimum annual streamflow; and the date of the center of volume (the date on which 50 percent of the annual streamflow has passed by a streamgage). Seasonal metrics were calculated for Fall (October-December), Winter (January-March), Spring (April-June), and Summer (July-September) and include mean and median seasonal streamflow, 1-day and 7-day maximum seasonal streamflow, and 1-day and 7-day minimum seasonal streamflow. Monthly metrics include mean and median monthly streamflow, 1-day and 7-day maximum monthly streamflow, and 1-day and 7-day minimum monthly streamflow. Trend analyses using the Mann-Kendall test were completed on the annual, seasonal, and monthly metrics, which were passed through a series of data completeness filters to ensure robust trend analyses. Trend analyses were conducted for climate years 1982 through 2021 for low-flow metrics (where each climate year represents April – March), and trend analyses were conducted for water years 1982 through 2021 for all other metrics (where each water year represents October – September).

The U.S. Geological Survey (USGS), in cooperation with the Wyoming Water Development Office, developed streamflow statistics for active (through September 30, 2021) and discontinued USGS streamgages in and near Wyoming with 10 or more years of daily mean streamflow record. The computation of streamflow statistics for USGS streamgages is part of a larger study to develop a StreamStats application (www.usgs.gov/streamstats) for the State of Wyoming (https://www.usgs.gov/centers/wyoming-montana-water-science-center/science/wyoming-streamstats). StreamStats is a web-based computer program that can be used to delineate drainage areas, determine basin characteristics, and compute streamflow statistics at locations with and without streamgages (https://streamstats.usgs.gov/ss/; Ries and others, 2024). Streamflow at each streamgage was assessed for degree of human alteration owing to dams and diversions before streamflow statistics were computed. Streamflow records from 631 streamgage periods of record were used to compute basic, seasonal, and flow-duration statistics; records for 390 streamgage periods of record were used to compute n-day statistics and statistics that can be used for regional regression. Methods used to compute the summary statistics contained in this data release are described in an accompanying report (Armstrong and others, 2025).

The U.S. Geological Survey (USGS), in cooperation with the Wyoming Water Development Office, developed streamflow statistics for active (through September 30, 2021) and discontinued USGS streamgages in and near Wyoming with 10 or more years of daily mean streamflow record. The computation of streamflow statistics for USGS streamgages is part of a larger study to develop a StreamStats application (www.usgs.gov/streamstats) for the State of Wyoming (https://www.usgs.gov/centers/wyoming-montana-water-science-center/science/wyoming-streamstats). StreamStats is a web-based computer program that can be used to delineate drainage areas, determine basin characteristics, and compute streamflow statistics at locations with and without streamgages (https://streamstats.usgs.gov/ss/; Ries and others, 2024). Streamflow at each streamgage was assessed for degree of human alteration owing to dams and diversions before streamflow statistics were computed. Streamflow records from 631 streamgage periods of record were used to compute basic, seasonal, and flow-duration statistics; records for 390 streamgage periods of record were used to compute n-day statistics and statistics that can be used for regional regression. Methods used to compute the summary statistics contained in this data release are described in an accompanying report (Armstrong and others, 2025).

This child item includes daily mean streamflow data obtained from the U.S. Geological Survey (USGS) National Water Information System database (https://doi.org/10.5066/F7P55KJN) and subsequently used in the computation of streamflow statistics. Daily mean streamflow data for some streamgages were removed from the analyses if the daily streamflows were determined to be incorrect, estimated, or had other problems. Streamflow at each streamgage was assessed for degree of human alteration owing to dams and diversions before streamflow statistics were computed. Methods used to remove daily mean streamflows, assess alteration, and compute the summary statistics contained in this data release are described in an accompanying report (Armstrong and others, 2025). Daily mean streamflow data for the period of record at each USGS streamgage used in the analyses are grouped into 15 folders organized by the 4-digit hydrologic unit code (HUC; https://water.usgs.gov/GIS/huc.html) in which the streamgage is located. The content of these folders is described in this metadata file. A table describing characteristics of the streamgages used in the analyses is provided in text file "AtSite_Table1_StreamgageSummary.txt."

The U.S. Geological Survey (USGS), in cooperation with the Wyoming Water Development Office, developed streamflow statistics for active (through September 30, 2021) and discontinued USGS streamgages in and near Wyoming with 10 or more years of daily mean streamflow record. The computation of streamflow statistics for USGS streamgages is part of a larger study to develop a StreamStats application (www.usgs.gov/streamstats) for the State of Wyoming (https://www.usgs.gov/centers/wyoming-montana-water-science-center/science/wyoming-streamstats). StreamStats is a web-based computer program that can be used to delineate drainage areas, determine basin characteristics, and compute streamflow statistics at locations with and without streamgages (https://streamstats.usgs.gov/ss/; Ries and others, 2024). Streamflow at each streamgage was assessed for degree of human alteration owing to dams and diversions before streamflow statistics were computed. Streamflow records from 631 streamgage periods of record were used to compute basic, seasonal, and flow-duration statistics; records for 390 streamgage periods of record were used to compute n-day statistics and statistics that can be used for regional regression. Methods used to compute the summary statistics contained in this data release are described in an accompanying report (Armstrong and others, 2025).

This child item includes daily mean streamflow data obtained from the U.S. Geological Survey (USGS) National Water Information System database (https://doi.org/10.5066/F7P55KJN) and subsequently used in the computation of streamflow statistics. Daily mean streamflow data for some streamgages were removed from the analyses if the daily streamflows were determined to be incorrect, estimated, or had other problems. Streamflow at each streamgage was assessed for degree of human alteration owing to dams and diversions before streamflow statistics were computed. Methods used to remove daily mean streamflows, assess alteration, and compute the summary statistics contained in this data release are described in an accompanying report (Armstrong and others, 2025). Daily mean streamflow data for the period of record at each USGS streamgage used in the analyses are grouped into 15 folders organized by the 4-digit hydrologic unit code (HUC; https://water.usgs.gov/GIS/huc.html) in which the streamgage is located. The content of these folders is described in this metadata file. A table describing characteristics of the streamgages used in the analyses is provided in text file "AtSite_Table1_StreamgageSummary.txt."

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.

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)

This dataset consists of daily streamflow percentiles for 1981-10-01 to 2020-03-31 relevant to streamflow drought defined using two approaches: Percentiles accounting for flow seasonality (variable threshold percentiles) and those based on the full record of data for each site regardless of season (fixed threshold percentiles). Because of the size of this dataset (99,530,836 rows), it could not be provided as a .csv file, and is instead provided as a .parquet file. Instructions on reading this file using the R programming language are provided in the Processing Step section of this metadata. The daily streamflow percentiles were estimated for ungaged areas of the Colorado River Basin (CRB) using neural network models, specifically long short-term memory (LSTM) models, by scientists on the USGS Data-Driven Drought Prediction project. The models were trained on data from 391 streamgages in the CRB and surrounding region and then used to generate predictions at ungaged stream locations within the CRB. Data from 01-Oct-1981 to 31-Mar-2014 was used to train the model with validation over the period of record spanning 01-Apr-2014 to 31-Mar- 2020. The models use explanatory variable inputs described in Wieczorek (2023) (doi.org/10.5066/P98IG8LO) to predict daily streamflow and streamflow percentiles as described in Simeone (2022) (doi.org/10.5066/P92FAASD). Model predictions are provided for 3,539 ungaged area spatial units from the National Hydrologic Geospatial Fabric version 1.1 (Bock et al., 2020) across the CRB. A follow up set of predictions is planned, with those predictions based on a models using a greater number of predictor variables including variables quantifying human flow alteration.