Advancing Machine Learning for Climate and Water Resilience: Techniques for Precipitation Forecasting

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ORIGINAL RESEARCH

Accepted on 30 Nov 2025

Machine Learning Generated Streamflow Drought Forecasts for the Conterminous United States (CONUS): Developing and Evaluating an Operational Tool to Enhance Sub-seasonal to Seasonal Streamflow Drought Early Warning for Gaged Locations

John Hammond
Phillip Goodling
Jeremy Diaz
Hayley Corson-Dosch
Aaron Heldmyer
Scott Hamshaw
Ryan McShane
Jesse Ross
Roy Sando
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Jacob Zwart

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Frontiers in Water

Frontiers in Water

Water and Artificial Intelligence
Water and Climate

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