Accelerating Urban Flood Inundation Simulation Under Spatio‐Temporally Varying Rainstorms Using ConvLSTM Deep Learning Model

Accelerating Urban Flood Inundation Simulation Under Spatio‐Temporally Varying Rainstorms Using ConvLSTM Deep Learning Model

Abstract Urban floods induced by rainstorms can lead to severe losses of lives and property, making rapid flood prediction essential for effective disaster prevention and mitigation. However, traditional deep learning (DL) models often overlook the spatial heterogeneity of rainstorms and lack interp...

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Bibliographic Details
Main Authors: Yaoxing Liao, Zhaoli Wang, Haijun Yu, Weizhi Gao, Zhaoyang Zeng, Xuefang Li, Chengguang Lai
Format: Article
Language:English
Published: Wiley 2025-08-01
Series:Water Resources Research
Subjects:
urban flood
rapid prediction
deep learning
ConvLSTM model
Grad‐CAM technique
Online Access:https://doi.org/10.1029/2025WR040433
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https://doi.org/10.1029/2025WR040433

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