Compound Flood Risk Assessment of Extreme Rainfall and High River Water Level
Urban flooding is typically caused by multiple factors, with extreme rainfall and rising water levels in receiving bodies both contributing to increased flood risks. This study focuses on assessing urban flood risks in Jinhua City, Zhejiang Province, China, considering the combined effects of extreme rainfall and high river water levels. Using historical data from Jinhua station (2005–2022), the study constructed a joint probability distribution of rainfall and water levels via a copula function. The findings show that the risk probability of combined rainfall and high water levels is significantly higher than considering each factor separately, indicating that ignoring their interaction could greatly underestimate flood risks. Scenario simulations using the Infoworks ICM model demonstrate that flood areas range from 0.67% to 5.39% under the baseline scenario but increase to 8.98–12.80% when combined with a 50a return period water level. High river water levels play a critical role in increasing both the extent and depth of flooding, especially when low rainfall coincides with high water levels. These findings highlight the importance of considering compound disaster-causing factors in flood risk assessment and can serve as a reference for urban drainage and flood control planning and risk management.
Authors
- Wanchun Li (ORCID: https://orcid.org/0009-0007-1653-759X)
- Shaoxuan Hou
- Yongwei Gong (ORCID: https://orcid.org/0000-0001-5439-6635)
- Jiangming Mo (ORCID: https://orcid.org/0000-0001-5156-5739)
- Chengbo Wang
- Xin Dang (ORCID: https://orcid.org/0000-0002-3372-3825)
- Honghong Shi
Institutions
- Energy Foundation (CN)
- Beijing University of Civil Engineering and Architecture (CN)
Publication Details
- Journal
- Water
- Published
- 2025-03-14
- DOI
- https://doi.org/10.3390/w17060841
- Citations
- 2
- Primary Topic
- Flood Risk Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 2.21
Funders
- National Natural Science Foundation of China