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    • Extreme gradient boosting machine learning models, suspended sediment, bedload, streamflow, and geospatial data, Minnesota, 2007-2019

    Metadata Updated: October 30, 2025

    A series of machine learning (ML) models were developed for Minnesota. The ML models were trained and tested using suspended sediment, bedload, streamflow, and geospatial data to predicted suspended sediment and bedload. Suspended sediment, bedload, and streamflow data were collected during water years 2007 through 2019. The ML models were used to improve understanding of sediment transport processes and increase accuracy of estimating sediment and loads for streams and rivers across Minnesota. The contents of this data release include README files, input files, output files, and source code (R software version 3.6.1) needed to reproduce the ML models and results in the associated article in Hydrological Processes (https://doi.org/10.1002/hyp.14648).

    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 14, 2025
    Metadata Updated Date October 30, 2025

    Metadata Source

    Harvested from DOI USGS DCAT-US

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date September 14, 2025
    Metadata Updated Date October 30, 2025
    Publisher U.S. Geological Survey
    Maintainer
    Identifier http://datainventory.doi.gov/id/dataset/usgs-61572adcd34e0df5fb9f8300
    Data Last Modified 2022-08-11T00:00:00Z
    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 40037bdf-f916-4484-a84c-9242554fe82c
    Harvest Source Id 2b80d118-ab3a-48ba-bd93-996bbacefac2
    Harvest Source Title DOI USGS DCAT-US
    Metadata Type geospatial
    Old Spatial -97.5929662585258, 43.1421712434946, -89.4191381335258, 49.4476743069444
    Source Datajson Identifier True
    Source Hash 853fb9a082b321a1c11d503ddb8210ee1f743a588866d566b49312a723a3d2db
    Source Schema Version 1.1
    Spatial {"type": "Polygon", "coordinates": -97.5929662585258, 43.1421712434946, -97.5929662585258, 49.4476743069444, -89.4191381335258, 49.4476743069444, -89.4191381335258, 43.1421712434946, -97.5929662585258, 43.1421712434946}

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