Urban Flood Risk Assessment Based on Dynamic Population Distribution and Fuzzy Comprehensive Evaluation

Hao Chen, Zongxue Xu (), Yang Liu, Yixuan Huang and Fang Yang
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Hao Chen: College of Water Sciences, Beijing Normal University, Beijing 100875, China
Zongxue Xu: College of Water Sciences, Beijing Normal University, Beijing 100875, China
Yang Liu: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100875, China
Yixuan Huang: College of Water Sciences, Beijing Normal University, Beijing 100875, China
Fang Yang: The Pear River Hydraulic Research Institute, Pearl River Water Resources Commission, Guangzhou 510000, China

IJERPH, 2022, vol. 19, issue 24, 1-17

Abstract: Floods are one of the most common natural disasters that can cause considerable economic damage and loss of life in many regions of the world. Urban flood risk assessment is important for urban flood control, disaster reduction, and risk management. In this study, a novel approach for assessing urban flood risk was proposed based on the dynamic population distribution, improved entropy weight method, fuzzy comprehensive evaluation method, and the principle of maximum membership, and the spatial distribution of flood risk in four different sessions or daily time segments (TS1–TS4) in the northern part of the Shenzhen River Basin (China) was assessed using geographic information system technology. Results indicated that risk levels varied with population movement. The areas of highest risk were largest in TS1 and TS3, accounting for 7.03% and 7.07% of the total area, respectively. The areas of higher risk were largest in TS2 and TS4, accounting for 4.54% and 4.64% of the total area, respectively. The findings of this study could provide a theoretical basis for assessing urban flood risk management measures in Shenzhen (and even throughout China), and a scientific basis for development of disaster prevention and reduction strategies by flood control departments.

Keywords: urban flood risk assessment; dynamic population; improved entropy weight; fuzzy comprehensive evaluation; principle of maximum membership (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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