The dataset contain estimates of natural monthly streamflow for 135,118 stream segments in California, USA, from 1950 to 2012. Segments are identified per the medium resolution National Hydrography Dataset (NHD), Version 1. The dataset also contains observed monthly streamflows and estimates of natural monthly streamflows for 894 USGS stream gages in California, USA.

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 includes simulated streamflow and sediment discharge for major tributaries contributing to Clear Lake, California. Historical hourly streamflow and sediment for each tributary location were outputs from an Hydrological Simulation Program - FORTRAN (HSPF) model. The historical data is available at an hourly time step from October 1980 to March 2024. The future time series were generated from the calibrated historical HSPF model and four CMIP6 bias corrected climate change scenarios: EC-Earth3, MPI-ESM1-2-HR, MIROC6, and TaiESM1, each using the" business as usual or medium warming scenarios from the SSP370 emissions forcing and socioeconomic pathway. The daily data are available for the same locations but at a daily time step from October 1980 to September 2099. Model inputs and outputs for each of the 11 sub models are located in the Model Archive child item.

This report summarizes estimates of “natural” and “unimpaired” flows for all areas in the Central Valley tributary to the Sacramento – San Joaquin Delta (Delta) for the period spanning water years 1922-2014. A major objective of this report is to clarify the conceptual differences between natural and unimpaired flows. In spite of the Department’s previous attempts to distinguish between natural conditions and its calculation of theoretical unimpaired flows, unimpaired flow estimates have frequently been used as a surrogate measure of natural conditions, presumably because natural flow estimates were unavailable. This report contains the Department’s first published estimates of natural flows; these estimates are derived from complex simulation models and are based on published estimates of natural vegetation cover and associated evapotranspiration.

This report summarizes estimates of “natural” and “unimpaired” flows for all areas in the Central Valley tributary to the Sacramento – San Joaquin Delta (Delta) for the period spanning water years 1922-2014. A major objective of this report is to clarify the conceptual differences between natural and unimpaired flows. In spite of the Department’s previous attempts to distinguish between natural conditions and its calculation of theoretical unimpaired flows, unimpaired flow estimates have frequently been used as a surrogate measure of natural conditions, presumably because natural flow estimates were unavailable. This report contains the Department’s first published estimates of natural flows; these estimates are derived from complex simulation models and are based on published estimates of natural vegetation cover and associated evapotranspiration.

The hydrologic modeling approach used to predict functional flows relies on daily streamflow data from gages operated by the U.S. Geological Survey (USGS) in California. This dataset contains, for each of 219 gages, a collection of metrics computed on each water year for the period of record to and including Water Year 2016.

The hydrologic modeling approach used to predict functional flows relies on daily streamflow data from gages operated by the U.S. Geological Survey (USGS) in California. This dataset contains, for each of 219 gages, a collection of metrics computed on each water year for the period of record to and including Water Year 2016.

This data set includes 28 physical watershed attributes for each of 135,118 stream segments (National Hydrodraphy Dataset, Version 1) in California. These data were used to support a report entitled: "Classification of California streams using combined deductive and inductive approaches: setting the foundation for analysis of hydrologic alteration" authored by Pyne, Carlisle, Konrad, and Stein, and published in the journal Ecohydrology. Specifically, these data were used in a classification (ie, cluster) analysis to identify unique groupings of watersheds with similar hydrological characteristics.

This data set includes 28 physical watershed attributes for each of 135,118 stream segments (National Hydrodraphy Dataset, Version 1) in California. These data were used to support a report entitled: "Classification of California streams using combined deductive and inductive approaches: setting the foundation for analysis of hydrologic alteration" authored by Pyne, Carlisle, Konrad, and Stein, and published in the journal Ecohydrology. Specifically, these data were used in a classification (ie, cluster) analysis to identify unique groupings of watersheds with similar hydrological characteristics.