Developing a Hybrid Modeling and Multivariate Analysis Framework for Storm Surge and Runoff Interactions in Urban Coastal Flooding

Document Type



The formation of urban coastal flooding is mainly ruled by the interaction between rainfall-runoff and storm surge. This study aims to advance the understanding of coastal urban flood mechanism by developing an integrated modeling and multivariate analysis framework, which involves a hydrologic model (Storm Water Management Model (SWMM)), as the core model, coupled with a coastal hydrodynamic model (Delft3D). The uncertainty associated with the flood depth prediction by integrated models is analyzed using the multivariate Gaussian Copula. The performance of the integrated modeling framework is evaluated for the Chittagong City of Bangladesh, which has experienced extreme and frequent coastal urban floods. Results from modeling indicate that changes in the tidal phase of coastal urban flooding alter the flood ’s duration and depth. The intensity of compound flooding is higher for the co-occurrence of rainfall and surge peaks than the occurrenceof both events in succession. The average flood duration and depth can be increased by about 2.5 h and 0.24 m, respectively, during compound events. When the storm surge occurs during the transition phase, between high/low tides (2–4 h before peak low/high tide), the duration of flood extends due to longer surge duration (4–4.5 h). Finally, the multivariate Gaussian Copula model adjusts the integrated modeling outputs and enhances the skill to predictthe inundation depth by 4.6–24.3%. The findings of this study are criticalfor a better understanding of coastal urban flood processes and enhancing the informed decision-making for emergency management and planning in lowlying coastal regions.

Digital Object Identifier (DOI)

APA Citation

Hasan Tanim, A., & Goharian, E. (2021). Developing a hybrid modeling and multivariate analysis framework for storm surge and runoff interactions in urban coastal flooding. Journal of Hydrology, 595, 125670.


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