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: Bridging Return Period Gaps in Flood Inundation Mapping Using a Hybrid Deep Learning Approach (AGU25)

Bridging Return Period Gaps in Flood Inundation Mapping Using a Hybrid Deep Learning Approach

Faezeh Maghsoodifar1,2, Md Shadman Sakib3, Mohamed Mowafy4, Haotian Wang5, Sagy Cohen6, Yinphan Tsang7, Hamed Moftakhari1,2, David F Muñoz8, Patrick Ray4 and Fangni Lei5, (1)The University of Alabama, Department of Civil, Construction, and Environmental Engineering, Tuscaloosa, United States, (2)The University of Alabama, Center for Complex Hydrosystems Research, Tuscaloosa, United States, (3)Virginia Polytechnic Institute and State University, Civil and Environmental Engineering, Blacksburg, United States, (4)University of Cincinnati, Environmental Engineering, Cincinnati, United States, (5)University of Connecticut, Civil and Environmental Engineering, Storrs, United States, (6)The University of Alabama, Department of Geography and the Environment, Tuscaloosa, AL, United States, (7)University of Hawaiʻi at Mānoa, Natural Resources and Environmental Management, Honolulu, United States, (8)Virginia Polytechnic Institute and State University, Civil & Environmental Engineering, Blacksburg, United States