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This dataset includes raw hydrologic data (streamflow data, groundwater level data, precipitation data) and geochemical data (geochemical results, fluorometric monitoring results) collected from January 1st, 2000 to December 31st, 2020 This dataset also includes interpreted results described in a U.S. Geological Survey Scientific Investigation Report (Goodling and others, 2023). This report describes how the hydrologic data were analyzed to calculate a water budget and how the geochemical data were interpreted. Goodling, P.J., Fleming, B.J., Solder, J., Soroka, A., and Raffensperger, J., 2023, Hydrogeologic characterization of Area B, Fort Detrick, Maryland: U.S. Geological Survey Scientific Investigations Report...
Categories: Data;
Tags: Frederick County,
Geophysics,
Hydrology,
Maryland,
USGS Science Data Catalog (SDC),
This data release contains the output of the National Hydrologic Hydrologic Model (NHM) version 1.0 aggregated to twelve-digit and ten-digit Hydrologic Unit Code (HUC) boundaries contained in the NHDPlus v2.1 dataset. The data are intended to provide "local" water budgets for each HUC boundary as total aggregated streamflow across HUC boundaries is not included. The HUC boundaries are periodically updated; this data release uses HUC boundaries downloaded on 10-26-2020. The NHM outputs aggregated in this release are calibrated using a step-wise calibration procedure to determine optimal parameter set and utilize the Muskingum routing (referred to as byHRU Musk-Obs). See Hay and LaFontaine (2020) for additional information...
Categories: Data;
Tags: Hydrologic processes,
Hydrology,
Hydrology,
USGS Science Data Catalog (SDC),
United States,
This metadata record describes model outputs and supporting model code for the Data-Driven Drought Prediction project of the Water Resources Mission Area Drought Program. The data listed here include outputs of multiple machine learning model types for predicting hydrological drought at select locations within the conterminous United States. The child items referenced below correspond to different models and spatial extents (Colorado River Basin region or conterminous United States). See the list below or metadata files in each sub-folder for more details. Daily streamflow percentile predictions for the Colorado River Basin region — Outputs from long short-term memory (LSTM) deep learning models corresponding to...
This data release contains model inputs, R code, and model outputs for predicting depth to bedrock in the Delaware River Basin at a 1km gridded resolution with a random forest model. Model inputs are provided in a comma-separated value (csv) file. The training data used in this study of 72,773 point observations of depth to bedrock (DTB) within the Delaware River Basin (DRB) that was compiled from several sources. These data were attributed with 15 predictor variables representing topographic, soil, geologic, and physiographic characteristics of the depth to bedrock observation. One predictor variable is a grouped surficial geology category that was adapted from the State Geologic Map Compilation (Horton and others,...
This model archive documents the Soil-Water-Balance (SWB) model used to simulate potential recharge for portions of Pennsylvania and Maryland from 2000 to 2021. The Pennsylvania and Maryland SWB model was used to create output at a 250 meter grid scale. Model parameters were adjusted using baseflow estimates from 36 reference watersheds varying in area from 0.37 to 817 square miles. The simulations were used to create 21-year grids of annual potential recharge and evapotranspiration, and the sensitivity of the model to parameter adjustments. The model archive includes all the files used in the sensitivity model runs, which are described in the accompanying Scientific Investigations Report 2022-5054. The directory...
The U.S. Geological Survey (USGS) Water Mission Area (WMA) is working to address a need to understand where the Nation is experiencing water shortages or surpluses relative to the demand for water need by delivering routine assessments of water supply and demand. It is also improving understanding of the natural and human factors affecting the balance between supply and demand. A key part of these national assessments is identifying long-term trends in water availability, including groundwater and surface water quantity, quality, and use. To describe the long-term trends in the surface water quality component of water availability, data from the USGS and other Federal, State, and local agencies were accessed primarily...
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