Filters: Contacts: {oldPartyId:11130} (X) > partyWithName: Upper Midwest Water Science Center (X) > Types: OGC WMS Service (X)

Filters Date Range Past year (0) Past month (0) Past week (0) Past day (0) Custom range... To   Search Types Map Service (1) OGC WFS Layer (1) OGC WMS Layer (1) Contacts Stephen M Westenbroek Brian K Breaker U.S. Geological Survey Benjamin J Dietsch U.S. Geological Survey - ScienceBase Water Resources Categories Data (1) Tag Types USGS Scientific Topic Keyword (1) Harvest Set (1) View Results as: JSON ATOM CSV

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 This data release contains datasets developed for the purpose of training and applying random forest models to the Mississippi Embayment Regional Study Area. 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 2022-5079) 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. Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Hydrology, USGS Science Data Catalog (SDC), Water Resources