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Lou Y, Wang P, Li Y, Zhang Y, Xie B, Hu T. Projecting urban flood risk through hydrodynamic modeling under shared socioeconomic pathways. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 370:122647. [PMID: 39357437 DOI: 10.1016/j.jenvman.2024.122647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 09/13/2024] [Accepted: 09/22/2024] [Indexed: 10/04/2024]
Abstract
Under future climate change, accurate risk assessment of urban flooding disasters is paramount for effective adaptation and mitigation strategies. However, conventional indicator-based assessment methods often fall short of accurately capturing the complexity of flooding dynamics. Current research predominantly focuses on predicting future hazard shifts while overlooking changes in other critical indicators. In this study, we establish a comprehensive index system for risk assessment, and quantified future changes in most indicators, utilizing the InfoWorks ICM model for hazard simulation and the CLUMondo model for land use predictions. Based on risk assessment results and regional characteristics, we further analyze the key factors driving future risk and discuss corresponding measures. The results indicate an exacerbation of future urban flood risk, with an 18% increase in high risk areas, primarily concentrated in the center of the study area. The dominant indicators are inundation depth and land use over the whole study area. However microtopography significantly affects risk in low-lying areas. Overall, under higher emission scenarios, the influence of GDP and population rises. These findings offer methodological insights for future urban flood risk assessment research and provide policymakers with valuable guidance to develop targeted adaptation measures in response to climate change.
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Affiliation(s)
- Yihan Lou
- Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Yuhangtang Road No. 2318, Hangzhou, 311121, China; Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou Normal University, Yuhangtang Road No. 2318, Hangzhou, 311121, China
| | - Pin Wang
- Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Yuhangtang Road No. 2318, Hangzhou, 311121, China; Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou Normal University, Yuhangtang Road No. 2318, Hangzhou, 311121, China
| | - Yao Li
- Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500AE Enschede, the Netherlands
| | - Yindong Zhang
- Zhejiang Academy of Emergency Management Science, China; Zhejiang Key Laboratory of Safety Engineering and Technology, China
| | - Bin Xie
- Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Yuhangtang Road No. 2318, Hangzhou, 311121, China; Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou Normal University, Yuhangtang Road No. 2318, Hangzhou, 311121, China.
| | - Tangao Hu
- Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Yuhangtang Road No. 2318, Hangzhou, 311121, China; Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou Normal University, Yuhangtang Road No. 2318, Hangzhou, 311121, China
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