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    • Stochastic Empirical Loading and Dilution Model in MS Access created for U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir20195053

    Metadata Updated: November 19, 2025

    Stochastic Empirical Loading and Dilution Model (SELDM) utilizes Microsoft Access databases to build and run model simulations. The compiled database was used for all simulations related to the publication: Stonewall, A.J., and Granato, G.E., 2018, Assessing potential effects of highway and urban runoff on receiving streams in total maximum daily load watersheds in Oregon using the Stochastic Empirical Loading and Dilution Model: U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir20195053

    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 13, 2025
    Metadata Updated Date November 19, 2025

    Metadata Source

    Harvested from DOI USGS DCAT-US

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date September 13, 2025
    Metadata Updated Date November 19, 2025
    Publisher U.S. Geological Survey
    Maintainer
    Identifier http://datainventory.doi.gov/id/dataset/usgs-5d03d46ce4b0e3d31158059b
    Data Last Modified 2024-01-18T00:00:00Z
    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 76d4bdcf-f7b5-40c3-a284-c0f28030008a
    Harvest Source Id 2b80d118-ab3a-48ba-bd93-996bbacefac2
    Harvest Source Title DOI USGS DCAT-US
    Metadata Type geospatial
    Source Datajson Identifier True
    Source Hash faeddd1a573755988a71c41142b981f6cfc8dafacf7124c33d20a2af31ab7bb8
    Source Schema Version 1.1

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