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International Journal of Disaster Risk Science
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Analysis of Urban Flooding Driving Factors Based on Water Tracer Method and Optimal Parameters-Based Geographical Detector

Authors: Kui Xu; Yizhuang Tian; Lingling Bin; Hongshi Xu; Xiao Xue; Jijian Lian;

Analysis of Urban Flooding Driving Factors Based on Water Tracer Method and Optimal Parameters-Based Geographical Detector

Abstract

Abstract Urban flooding is caused by multiple factors, which seriously restricts the sustainable development of society. Understanding the driving factors of urban flooding is pivotal to alleviating flood disasters. Although the effects of various factors on urban flooding have been extensively evaluated, few studies consider both interregional flood connection and interactions between driving factors. In this study, driving factors of urban flooding were analyzed based on the water tracer method and the optimal parameters-based geographical detector (OPGD). An urban flood simulation model coupled with the water tracer method was constructed to simulate flooding. Furthermore, interregional flood volume connection was analyzed based on simulation results. Subsequently, driving force of urban flooding factors and interactions between them were quantified using the OPGD model. Taking Haidian Island in Hainan Province, China as an example, the coupled model simulation results show that sub-catchment H6 is the region experiencing the most severe flooding and sub-catchment H9 contributes the most to overall flooding in the study area. The results of subsequent driving effect analysis show that elevation is the factor with the maximum single-factor driving force (0.772) and elevation ∩ percentage of building area is the pair of factors with the maximum two-factor driving force (0.968). In addition, the interactions between driving factors have bivariable or nonlinear enhancement effects. The interactions between two factors strengthen the influence of each factor on urban flooding. This study contributes to understanding the cause of urban flooding and provides a reference for urban flood risk mitigation.

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Keywords

Urban flood simulation model, Driving factors, TA495, Hainan, Urban flooding, Disasters and engineering, Optimal parameters-based geographical detector (OPGD), Water tracer method

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
gold