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Machine Learning Modeling of Water Quality Based Risk Assessment

Metadata Updated: March 29, 2021

This is the geospatial and hydroclimate input data used to develop data-driven Machine Learning (ML) models as well as model estimated water quality based risk metrics and watershed health composite measure in three river basins in the Midwest. Model outputs that are used to construct the figures in the paper are displayed in the Excel file with the definitions of the data reported in each datasheet. The directory to the GIS data that were used to construct the inputs and spatially distributed risk metrics at the HUC-10 level is listed here and in the Scientific Data Management Plan. Portions of this dataset are inaccessible because: Large size GIS database. They can be accessed through the following means: C:\Users\MHantush\OneDrive - Environmental Protection Agency (EPA)\ScienceHUB\WH ML Modeling. Format: Generic GIS database.

Access & Use Information

Public: This dataset is intended for public access and use. License: See this page for license information.

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Metadata Created Date March 29, 2021
Metadata Updated Date March 29, 2021

Metadata Source

Harvested from EPA ScienceHub

Additional Metadata

Resource Type Dataset
Metadata Created Date March 29, 2021
Metadata Updated Date March 29, 2021
Publisher U.S. EPA Office of Research and Development (ORD)
Data Last Modified 2019-10-17
Public Access Level public
Bureau Code 020:00
Schema Version
Harvest Object Id fd752875-7856-491c-be53-89c9506a54a2
Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
Harvest Source Title EPA ScienceHub
Program Code 020:096
Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
Source Datajson Identifier True
Source Hash 74a98755c446078044d7be9cbc86eb6bd5c26a0e
Source Schema Version 1.1

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