Stream Height Forecasts via NASA/SPoRT Machine Learning

Posted on: 2/18/2022

This training item serves as a reference for a stream height forecast product developed by NASA's Short-term Prediction, Research, and Transition (SPoRT) program. The product is derived from a machine learning (ML) model where inputs to the model include soil moisture values from the NASA SPoRT Land Information System (LIS) as well as QPE/QPF and stream gauge height. The Streamflow ML Height forecast product is intended for application in areas without existing forecast information and to provide an extended outlook (i.e. beyond 2 days) of stream flooding potential.


Author (s): Kevin Fuell (UAH), Andrew White (UAH), Kris White (NWS-HUN)
Language: English
Location: U.S. Southeast, East, Northeast
Date of event(s): Examples range from Fall to early Spring
Categories: Hydrology Flooding, Model Derived, NASA LIS

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