Potential impacts of storm surge-induced flooding based on refined exposure estimation: a case study in Zhoushan island, China

Abstract

Storm surge-induced flooding (SSIF) is a major hazard for coastal areas under intensified typhoons. Therefore, it is essential to assess the potential impacts of SSIF (SSPIA). This study proposes a multidisciplinary framework for refined SSPIA using an ocean model and a refined exposure estimation method. First, a finite-volume coastal ocean model (FVCOM) and a typhoon model were developed and validated. Then, five scenarios of varying intensity were defined and combined with FVCOM to identify inundation scenarios. Subsequently, machine learning was used to obtain the fine-scale gridded population and gross domestic product (GDP) maps based on the census and geospatial data. Finally, we assessed the magnitude of the affected population and GDP based on the inundation scenarios and refined exposure datasets. We selected Zhoushan Island as a study area to implement this framework. Our assessment results show that the lowest scenario (955 hPa) affected 2587 people and 323.745 million CNY of GDP, while the highest scenario (915 hPa) affected 259,516 people and 20,178.898 million CNY of GDP. Therefore, it is imperative to implement effective mitigation and adaptation measures to address the threat of SSIF. This framework will apply to all flood-prone areas for a refined assessment of the potential impacts of SSIF.