Assessing and zoning of typhoon storm surge risk with a geographic information system (GIS) technique: a case study of the coastal area of Huizhou

Abstract

Abstract. Storm surge is one of the most destructive marine disasters to life and property for Chinese coastal regions, especially for Guangdong Province. In Huizhou city, Guangdong Province, due to the high concentrations of chemical and petroleum industries and the high population density, the low-lying coastal area is susceptible to the storm surge. Therefore, a comprehensive risk assessment of storm surge over the coastal area of Huizhou can delimit zones that could be affected to reduce disaster losses. In this paper, typhoon intensity for the minimum central pressure of 880, 910, 920, 930, and 940 hPa (corresponding to a 1000-, 100-, 50-, 20-, and 10-year return period) scenarios was designed to cover possible situations. The Jelesnianski method and the Advanced Circulation (ADCIRC) model coupled with the Simulating Waves Nearshore (SWAN) model were utilized to simulate inundation extents and depths of storm surge over the computational domain under these representative scenarios. Subsequently, the output data from the coupled simulation model (ADCIRC–SWAN) were imported to the geographic information system (GIS) software to conduct the hazard assessment for each of the designed scenarios. Then, the vulnerability assessment was made based on the dataset of land cover types in the coastal region. Consequently, the potential storm surge risk maps for the designed scenarios were produced by combining hazard assessment and vulnerability assessment with the risk matrix approach. The risk maps indicate that due to the protection given by storm surge barriers, only a small proportion of the petrochemical industrial zone and the densely populated communities in the coastal areas were at risk of storm surge for the scenarios of 10- and 20-year return period typhoon intensity. Moreover, some parts of the exposed zone and densely populated communities were subject to high and very high risk when typhoon intensities were set to a 50- or a 100-year return period. Besides, the scenario with the most intense typhoon (1000-year return period) induced a very high risk to the coastal area of Huizhou. Accordingly, the risk maps can help decision-makers to develop risk response plans and evacuation strategies in coastal communities with a high population density to minimize civilian casualties. The risk analysis can also be utilized to identify the risk zones with the high concentration of chemical and petroleum industries to reduce economic losses and prevent environmental damage caused by the chemical pollutants and oil spills from petroleum facilities and infrastructures that could be affected by storm surge.

Numerical study of storm surge-induced coastal inundation in Laizhou Bay, China

“…Comparisons of wind field snapshots between CFS and ERA5 at 12:00 (UTC) on September 1, 1992 (A, C) and at 18:00 (UTC) on September 1, 1992 (B, D) during TY9216. 2020; Shi et al, 2021;Wang et al, 2021). The ADCIRC model is an advanced hydrodynamic model (Luettich et al, 1992), that obtains water level data and current data depending on the Generalized Wave Continuity Equation (GWCE) and the vertically integrated momentum equations.…”

Geospatial modeling of the tropical cyclone risk in the Guangdong Province, China

“…22 -25.52 N and 109.65 -117.32 E. The total terrain includes an area of 179800 km 2 and is mainly covered by arable land, forests, and coastal wetlands (Liu and Chen 2019). Guangdong is the most economically developed and populous region in southern China, with a total gross domestic product (GDP) of RMB 9.7 trillion and a permanent resident population of 113.46 million by the end of 2018 (Wang et al 2021). Guangdong is characterized by tropical and subtropical monsoon climate.…”

A quantitative method for the similarity assessment of typhoon tracks

“…Bui et al (2019) proposed and verified a new soft computing approach based on multivariate adaptive regression splines and particle swarm optimization for spatial prediction of flash flood susceptible areas at high-frequency tropical typhoon area. Wang et al (2021) semi-quantified the risk assessment of storm surge under different typhoon intensity and performed the assessment in ArcGIS by the coupled model ADCIRC-SWAN and the Jelesnianski method.…”