Journal article
Deep learning rapid flood risk predictions for climate resilience planning
Abstract
Floods have been causing the world’s costliest weather-related catastrophes and their magnitude and frequency are projected to increase even further due to climate change. Current flood risk quantification procedures include the use of complex and highly uncertain hydrologic-hydraulic models for hazard mapping and computationally-tedious manipulations for vulnerability evaluation—hindering urban centers climate resilience planning. Adopting a …
Authors
Yosri A; Ghaith M; El-Dakhakhni W
Journal
Journal of Hydrology, Vol. 631, ,
Publisher
Elsevier
Publication Date
March 2024
DOI
10.1016/j.jhydrol.2024.130817
ISSN
0022-1694