The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Hybrid Machine Learning Emulation of Coastal Flooding: Mesh-Wide Water Level Prediction and Wet/Dry Classification Using GPU Acceleration (AGU25)

Hybrid Machine Learning Emulation of Coastal Flooding: Mesh-Wide Water Level Prediction and Wet/Dry Classification Using GPU Acceleration

Sunghoon Han, Oregon State University, School of Civil and Construction Engineering, Corvallis, OR, United States, David Hill, Oregon State University, School of Civil & Construction Engineering, Corvallis, United States, Carter Howe, Oregon State University, School of Civil and Consruction Engineering, Corvallis, United States, David Honegger, US Army Corps of Engineers, Fort Wainwright, United States, Carson Williams, Oregon State University, College of Earth, Ocean, and Atmospheric Science, Corvallis, OR, United States, Peter Ruggiero, Oregon State University, College of Earth, Ocean, and Atmospheric Sciences, Corvallis, United States and Merrick C Haller, Oregon State University, Civil and Construction Engineering, Corvallis, OR, United States