Probabilistic Flood Hazard Assessment for Multiple Flood and Levee Breaching Scenarios: A Case Study of Etobicoke Creek, Canada

ABSTRACT Flood hazard assessment is crucial to mitigate the risks associated with flooding. Integrating levee failure scenarios into these assessments should improve the evaluation of flood risks and enhance the resilience of communities and infrastructure. This research presents a probabilistic flo...

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Bibliographic Details
Main Authors: Florence Mainguenaud, Usman T. Khan, Laurent Peyras, Claudio Carvajal, Bruno Beullac, Jitendra Sharma
Format: Article
Language:English
Published: Wiley 2025-03-01
Series:Journal of Flood Risk Management
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Online Access:https://doi.org/10.1111/jfr3.70002
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Summary:ABSTRACT Flood hazard assessment is crucial to mitigate the risks associated with flooding. Integrating levee failure scenarios into these assessments should improve the evaluation of flood risks and enhance the resilience of communities and infrastructure. This research presents a probabilistic flood hazard approach to assess levee failure and its impact on flood hazard. Our method includes a comprehensive assessment of backward erosion and overflowing failure mechanisms, integrated within a 1D/2D hydraulic model that simulates flood propagation and levee breaching. We calculate the cumulative probability of flood depth and velocity considering various scenarios, taking into account levee failure breaching for various failure mechanisms and several flood intensities. We apply the method to a residential area along Etobicoke Creek in Ontario, Canada. The results highlight which levee segment has the most impact on flood hazard, emphasizing the importance of incorporating levee failure scenarios in flood hazard assessments. The cumulative probability curve provides a more holistic result in locating the most hazardous areas rather than considering one return period or one failure mechanism. It can be expended to every location of the protected area, allowing for the creation of a probabilistic map for a desired probability.
ISSN:1753-318X