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Abstract: Evaluating the Reliability of Flood Inundation Mapping in Ungauged Locations Using Observed, Modeled, and Machine Learning-Based Hydrologic Data (AGU25)

Evaluating the Reliability of Flood Inundation Mapping in Ungauged Locations Using Observed, Modeled, and Machine Learning-Based Hydrologic Data

Junho Song1, Reza Saleh Alipour2, Savalan Naser Neisary3, Md. Shahabul Alam4, James Halgren4 and Steven J Burian5, (1)University of Alabama, Alabama Water Institute, Tuscaloosa, United States, (2)University of Alabama, Civil, Construction, and Environmental Engineering, Tuscaloosa, United States, (3)The University of Alabama, Department of Civil, Construction, and Environmental Engineering, Tuscaloosa, United States, (4)The University of Alabama, Alabama Water Institute, Tuscaloosa, United States, (5)Cooperative Institute for Research to Operations in Hydrology (CIROH), Alabama Water Institute, The University of Alabama, Tuscaloosa, AL, Alabama Water Institute, Tuscaloosa, United States
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