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Data-Driven Drought Prediction Project Model Outputs for Select Spatial Units within the Conterminous 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. 1. Daily streamflow percentile predictions for the Colorado River Basin region — Outputs from long short-term memory (LSTM) deep learning models corresponding to selected stream gage locations.

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Author(s) Scott D Hamshaw orcid, Thomas R Sando orcid, Phillip J Goodling orcid, Ryan R McShane orcid, William D Watkins orcid, Ellie White orcid
Publication Date 2023-04-28
Beginning Date of Data 1980-01-01
Ending Date of Data 2020-12-31
Data Contact
DOI https://doi.org/10.5066/P97NIH7Y
Citation Hamshaw, S.D., Sando, T.R., Goodling, P.J., McShane, R.R., Watkins, W.D., and White, E., 2023, Data-Driven Drought Prediction Project Model Outputs for Select Spatial Units within the Conterminous United States: U.S. Geological Survey data release, https://doi.org/10.5066/P97NIH7Y.
Metadata Contact
Metadata Date 2023-04-28
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Citations of these data No citations of these data are known at this time.
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License http://www.usa.gov/publicdomain/label/1.0/
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Harvest Source: ScienceBase
Harvest Date: 2025-01-07T16:23:15.254Z