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Model Archive and Data Release: Input data, trained model data, and model outputs for predicting streamflow and base flow for the Mississippi Embayment Regional Study Area using a random forest model

Published by U.S. Geological Survey | Department of the Interior | Catalog Last Checked: May 05, 2026 at 07:35 PM | Dataset Last Updated: May 05, 2022 at 12:00 AM
This data archive contains datasets developed for the purpose of training and applying random forest models to the Mississippi Embayment Regional Aquifer. The random forest models are designed to predict total stream flow and baseflow as a function of a combination of watershed characteristics and monthly weather data. These datasets are associated with a report (SIR 2022-xxxx) and code contained in a USGS GitLab repository. The GitLab repository (https://code.usgs.gov/map/maprandomforest/) contains much more information about how these data may be used to supply predictions of stream flow and baseflow.

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