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    • 3 Model Forcings: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins

    Metadata Updated: November 12, 2025

    <p>This data release component contains model inputs including river basin attributes, weather forcing data, and simulated and observed river discharge.</p>

    Access & Use Information

    Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

    Downloads & Resources

    Dates

    Metadata Created Date September 12, 2025
    Metadata Updated Date November 12, 2025

    Metadata Source

    Harvested from DOI USGS DCAT-US

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date September 12, 2025
    Metadata Updated Date November 12, 2025
    Publisher U.S. Geological Survey
    Maintainer
    Identifier http://datainventory.doi.gov/id/dataset/usgs-6084cab2d34eadd49d31aeab
    Data Last Modified 2021-09-27T00:00:00Z
    Category geospatial
    Public Access Level public
    Bureau Code 010:12
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
    Metadata Catalog ID https://ddi.doi.gov/usgs-data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Harvest Object Id 0c64e44b-4800-400b-a71f-6f88b0128fe8
    Harvest Source Id 2b80d118-ab3a-48ba-bd93-996bbacefac2
    Harvest Source Title DOI USGS DCAT-US
    Metadata Type geospatial
    Old Spatial -124.138658984335, 29.1524975232233, -67.8714112090545, 49.0018341836332
    Source Datajson Identifier True
    Source Hash d274cd5382cb16412d445702299498a3c6e9c8a4312fdf89ad5a60e024f97881
    Source Schema Version 1.1
    Spatial {"type": "Polygon", "coordinates": -124.138658984335, 29.1524975232233, -124.138658984335, 49.0018341836332, -67.8714112090545, 49.0018341836332, -67.8714112090545, 29.1524975232233, -124.138658984335, 29.1524975232233}

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