Zhong, Ming, Li, Xiaodi, Wang, Jiao, Zhuo, Lu and Ling, Feng
2025.
Cascading landslide–barrier dam–outburst flood hazard: A systematic study using rockfall analyst and HEC-RAS.
Remote Sensing
17
(11)
, p. 1842.
10.3390/rs17111842
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Abstract
Landslide hazard chains pose significant threats in mountainous areas worldwide, yet their cascading effects remain insufficiently studied. This study proposes an integrated framework to systematically assess the landslide-landslide dam-outburst flood hazard chain in mountainous river systems. First, landslide susceptibility is assessed through a random forest model incorporating 11 static environmental and geological factors. The surface deformation rate derived from SABS-InSAR technology is incorporated as a dynamic factor to improve classification accuracy. Second, motion trajectories of rock masses in high-risk zones are identified by Rockfall Analyst model to predict potential river blockages by landslide dams, and key geometric parameters of the landslide dams are predicted using a predictive model. Third, the 2D HEC-RAS model is used to simulate outburst flood evolution. Results reveal that: (1) incorporating surface deformation rate as a dynamic factor significantly improves the predictive accuracy of landslide susceptibility assessment; (2) landslide-induced outburst floods exhibit greater destructive potential and more complex inundation dynamics than conventional mountain flash floods; and (3) the outburst flood propagation process exhibits three sequential phases defined by the Outburst Flood Arrival Time (FAT): initial rapid advancement phase, intermediate lateral diffusion phase, and mature floodplain development phase. These phases represent critical temporal thresholds for initiating timely downstream evacuation. This study contributes to the advancement of early warning systems aimed at protecting downstream communities from outburst floods triggered by landslide hazard chains. It enables researchers to better analyze the complex dynamics of such cascading events and to develop effective risk reduction strategies applicable in vulnerable regions.
Item Type: | Article |
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Date Type: | Published Online |
Status: | Published |
Schools: | Schools > Earth and Environmental Sciences |
Additional Information: | License information from Publisher: LICENSE 1: URL: https://creativecommons.org/licenses/by/4.0/, Start Date: 2025-05-25 |
Publisher: | MDPI |
Date of First Compliant Deposit: | 11 June 2025 |
Date of Acceptance: | 21 May 2025 |
Last Modified: | 11 Jun 2025 11:45 |
URI: | https://orca.cardiff.ac.uk/id/eprint/179002 |
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