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

Name: 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
Creator: U.S. Army Corps of Engineers; United States Geological Survey
Published: 2022-01-01T00:00:00+08:00

U.S. Geological Survey2022-01-01 更新2026-04-23 收录

水文预测

随机森林径流模拟

数据链接：

https://www.sciencebase.gov/catalog/item/5f32c66b82cee144fb313867 数据链接链接失效反馈

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资源简介：

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-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.

提供机构：

U.S. Army Corps of Engineers; United States Geological Survey

创建时间：

2022-01-01