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

    Metadata Updated: October 29, 2023

    <p>This data release component contains model code and configurations for the LSTM models used to predict stream temperature.</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 June 1, 2023
    Metadata Updated Date October 29, 2023

    Metadata Source

    Harvested from DOI EDI

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date June 1, 2023
    Metadata Updated Date October 29, 2023
    Publisher U.S. Geological Survey
    Maintainer
    @Id http://datainventory.doi.gov/id/dataset/3c4d4ac3e740364fe93eadb61db61fc8
    Identifier USGS:6084cb16d34eadd49d31aead
    Data Last Modified 20210927
    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://datainventory.doi.gov/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 9c02b524-efdf-4112-a236-7d9a82c9ff51
    Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
    Harvest Source Title DOI EDI
    Metadata Type geospatial
    Old Spatial -124.138658984335,29.1524975232233,-67.8714112090545,49.0018341836332
    Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
    Source Datajson Identifier True
    Source Hash bf79cc094d0257729c1e0b7f3f3807279c5e83bade7edcfdd5f2127c9f7eaa25
    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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