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This is accompanying data produced for the study "Implications of Model Selection: Inter-Comparison of Publicly-Available, CONUS-Extent Hydrologic Component Estimates". These datasets were converted from their primary structures (rasters and shapefiles) to EPA Ecoregions Level I. Conversion was performed by averaging timestep layers via mean area weight to produce a single vector of monthly values for each ecoregion, for each of the following hydrologic cycle components: precipitation (P), actual evapotranspiration (AET), runoff (R), snow water equivalent (SWE), rootzone soil moisture in equivalent water depth (RZSME), and rootzone soil moisture in volumetric water content (RZSMV).
Categories: Data;
Tags: USGS Science Data Catalog (SDC),
United States of America,
climate change,
evaporation,
precipitation (atmospheric),
A list of stream gages within the conterminous United States that will serve as the initial list of sites (version 1.0) used for streamflow benchmarking of hydrologic models. Sites within this list were chosen based on their presence in the GAGES-II dataset, their availability of modeled streamflow data from the most recent version of the National Hydrologic Model application of Precipitation-Runoff Modeling System v1.0, and their availability of modeled streamflow data from the most recent version of the NOAA National Water Model application of WRF-hydro version 2.1 retrospective dataset.
Categories: Data;
Tags: Climatology,
Hydrology,
Information Sciences,
USGS Science Data Catalog (SDC),
United States,
This data release provides rasters of actual evapotranspiration (ET) at the Conterminous U.S. (CONUS) scale from October 1895 to September 2018. Data are provided at the annual and monthly time scales at 800 meter spatial resolution. The dataset was produced using ensemble estimation methods described in the associated journal article. The data release also includes associated datasets developed in the production of these ET estimates, including monthly maps of groundwater and surface water irrigation from 1980-2018, as well as data underlying the figures in the associated paper.
Categories: Data;
Tags: Hydrology,
USGS Science Data Catalog (SDC),
United States,
evaporation,
transpiration,
As more hydrocarbon production from hydraulic fracturing and other methods produce large volumes of water, innovative methods must be explored for treatment and reuse of these waters. However, understanding the general water chemistry of these fluids is essential to providing the best treatment options optimized for each producing area. Machine learning algorithms can often be applied to datasets to solve complex problems. In this study, we used the U.S. Geological Survey’s National Produced Waters Geochemical Database (USGS PWGD) in an exploratory exercise to determine if systematic variations exist between produced waters and geologic environment that could be used to accurately classify a water sample to a given...
Spatial data used in the study "Characterization and Evaluation of Controls on Post-Fire Streamflow Response Across Western U.S. Watersheds".
In this research, we characterized the changes in the Gravity Recovery and Climate Experiment (GRACE) monthly total water storage anomaly (TWSA) in 18 surface basins and 12 principal aquifers in the conterminous United States during 2003–2016. Regions with high variability in storage were identified. Ten basins and four aquifers showed significant changes in storage. Eight surface basins and eight aquifers were found to show decadal stability in storage. A pixel-based analysis of storage showed that the New England basin and North Atlantic Coastal Plain aquifer showed the largest area under positive storage change. By contrast, the Lower Colorado and California basins showed the largest area under negative change....
Categories: Publication;
Types: Citation
Spatially-referenced data used in the study "Rust, A.J., Saxe, S., McCray, J., Rhoades, C.C., Hogue, T.S., 2019. Evaluating the factors responsible for post-fire water quality response in forests of the western USA. Int. J. Wildland Fire.": Wildfires commonly increase nutrient, carbon, sediment, and metal inputs to streams yet the factors responsible for the type, magnitude and duration of water quality effects are poorly understood. Prior work by the current authors found increased nitrogen, phosphorus and cation exports were common the first 5 post-fire years from a synthesis of 159 wildfires across the western United States. In the current study, an analysis is undertaken to determine factors that best explain...
Categories: Data;
Tags: CONUS,
Continental United States,
Environmental Health,
Hydrogeology,
Land Use Change,
The impact of wildfire on water availability is a critical issue in the western United States. Because actual evapotranspiration (ETa) constitutes the largest loss in the terrestrial water budget, it has been suggested that fire-induced ETa reduction is a primary driver of elevated post-fire discharge. Ten gaged watersheds with burns exceeding 5% of their total contributing drainage area were selected from California, Oregon, Montana, Utah, New Mexico, and Colorado. Continuous daily stream gage data were compiled, and 30-meter ETa estimates were calculated with the Operational Simplified Surface Energy Balance (SSEBop) model. Fire-induced ETa shifts were quantified with statistical tests that compared pre and post-fire...
This data release contains the D-score (version 0.1) daily streamflow performance benchmark results for the National Hydrologic Model Infrastructure application of the Precipitation-Runoff Modeling System (NHM) version 1 "byObs" calibration with Muskingum routing computed at streamflow benchmark locations (version 1) as defined by Foks and others (2022). Model error was determined by evaluating predicted daily mean streamflow versus observed daily mean streamflow. Using those errors, the D-score performance benchmark computes the mean squared logarithmic error (MSLE), then decomposes the overall MSLE into orthogonal components such as bias, distribution, and sequence (Hodson and others, 2021). For easier interpretation,...
Categories: Data;
Tags: Data Release,
Hydrology,
Mean squared error,
Model evaluation,
Streamflow prediction,
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