Rainfall and coastal water level relative timing as drivers of compound flooding in Haikou, China

Study Region Urban area of Haikou, Hainan Province, China. Study focus Compound flooding in typhoon-prone coastal cities arises from the interaction between coastal water level and rainfall, but the role of their relative timing remains underexplored. This study proposes a framework that captures the relative timing for improved compound flooding assessment. Using the D -Flow FM model, we simulate 49 time-lag scenarios to quantify how timing ( ∆ t ) between coastal total water level and rainfall modulate inundation. For each scenario, we evaluate inundation volume and compute absolute ( ∆ M ) and relative ( ∆ R ) increments relative to the baseline. We delineate compound zones and decompose contributions from water level, rainfall, and their interaction. New hydrological insights for the region The results indicate that time-lags strongly shape compound flooding and produce nonlinear responses. Inundation is consistently larger when rainfall peaks before the coastal water level peak. A window from −19 h to −4 h yields volumes exceeding the historical event, and the maximum inundation occurs at −13 h with ∆ R = 9.44% and ( ∆ M = 8.53 million m³). Water level is the dominant driver, yet within compound zones, the interaction term exceeds rainfall alone. These findings highlight that taking ∆ t = 0 h as the worst-case can underestimate risks, emphasizing that the relative timing of rainfall and coastal water levels is a critical factor for managing compound flooding in coastal cities.

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Publication Details

Journal
Journal of Hydrology Regional Studies
Published
2026-06-13
DOI
https://doi.org/10.1016/j.ejrh.2026.103635
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Rainfall and coastal water level relative timing as drivers of compound flooding in Haikou, China

Can Lu, Patrick Willems, Hanqing Xu, Guofeng Wu et al.
Journal of Hydrology Regional Studies
Flood Risk Assessment and Management
article

Rainfall and coastal water level relative timing as drivers of compound flooding in Haikou, China

Can Lu, Patrick Willems, Hanqing Xu, Guofeng Wu, Yue Sheng, Qing Liu, Yi-Xiang Wang, Laixiang Sun, Hayley J. Fowler
article en

Abstract

Study Region Urban area of Haikou, Hainan Province, China. Study focus Compound flooding in typhoon-prone coastal cities arises from the interaction between coastal water level and rainfall, but the role of their relative timing remains underexplored. This study proposes a framework that captures the relative timing for improved compound flooding assessment. Using the D -Flow FM model, we simulate 49 time-lag scenarios to quantify how timing ( ∆ t ) between coastal total water level and rainfall modulate inundation. For each scenario, we evaluate inundation volume and compute absolute ( ∆ M ) and relative ( ∆ R ) increments relative to the baseline. We delineate compound zones and decompose contributions from water level, rainfall, and their interaction. New hydrological insights for the region The results indicate that time-lags strongly shape compound flooding and produce nonlinear responses. Inundation is consistently larger when rainfall peaks before the coastal water level peak. A window from −19 h to −4 h yields volumes exceeding the historical event, and the maximum inundation occurs at −13 h with ∆ R = 9.44% and ( ∆ M = 8.53 million m³). Water level is the dominant driver, yet within compound zones, the interaction term exceeds rainfall alone. These findings highlight that taking ∆ t = 0 h as the worst-case can underestimate risks, emphasizing that the relative timing of rainfall and coastal water levels is a critical factor for managing compound flooding in coastal cities.

Journal of Hydrology Regional StudiesVol. 66
University of London (GB), SOAS University of London (GB), Tyndall Centre (GB), East China Normal University (CN), University of Maryland, College Park (US), KU Leuven (BE)
National Natural Science Foundation of China, East China Normal University
Life below water, Climate action
Openalex Percentile: Top 7%
Flood Risk Assessment and Management
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