| The coastal regions of China are prone to many natural hazards,such as winds,storm surges,waves,and tsunamis,which cause economic damage and loss of human lives each year.Storm surge,as the greatest threat to life and property in China,have serious impacts on the economic development in the coastal areas.In recent decades,with considerably rising sea levels caused by continued global warming,the frequency and intensity of tropical cyclone have increased,and tropical cyclone-induced storm surge becomes more destructive.Therefore,it is important to make risk assessments to identify areas at risk and design risk reduction strategies,which can establish storm surge preparedness plans in advance to reduce economic losses and casualties for coastal cities.Based on previous research related to storm surge risk assessment,this paper proposed a comprehensive storm surge risk assessment integrated physical vulnerability and social vulnerability for the small-scale zone.With numerical simulation,geographic information system technology,machine learning methods,and principal component analysis,the storm surge risk assessment case study of Daya Bay,Huizhou was conducted.The main research points of the paper are as follows:(1)In this paper,the Jelesnianski method was utilized to generate wind field,and the Advanced Circulation(ADCIRC)hydrodynamic model coupled with the Simulating Waves Nearshore(SWAN)wave model was employed to simulate the storm surge.In order to assess the performance of the coupled model(ADCIRC–SWAN),the surge simulations during the different typhoon cases,which caused unusually high water levels in the study area,were compared with observations recorded by the gauging station.The results indicate that the absolute error is between 5-18 cm and the relative error is between2%-30%in the Huizhou gauging station and the absolute error is between 0-17 cm and the relative error is between 1%-17%in the Gangkou gauging station.Therefore,the performance of the coupled model is considered to be reliable regarding its ability to simulate storm surges in the study area.(2)Analysis of tropical cyclones in history that affected the coastal area of Huizhou,the probability of the annual occurrence(called the return period)for a given intensity associated with typhoon can be estimated.The 1000-year,100-year,50-year,20-year,and 10-year return periods are corresponding to the minimum central pressure of 880 h Pa,910 h Pa,920 h Pa,930 h Pa,and 940 h Pa,respectively.Subsequently,33 typhoon tracks deviating from the original Typhoon Mangkhut track were generated and five typhoon scenarios characterized by five different return periods were defined(1000-year,100-year,50-year,20-year,and 10-year return period).Then,the Jelesnianski model and the coupled model(ADCIRC+SWAN)were employed to simulate the storm surge for each of the defined typhoon scenarios.The results show that under different typhoon scenarios,the inundated depths of storm surge in the coastal area of Huizhou are varied.When the return period is 1000-year,the average inundated depth of storm surge is 5.78 m,which is significantly higher than those caused by other defined typhoons.The average inundated depths of storm surge,which were resulted from typhoons with the return periods of 100-year and 50-year,are 2.64 m and 2.39 m,respectively.The typhoons with the return periods of 20-year and 10-year led to the average inundated depths of storm surge at 2.22 m and 1.97 m,respectively.(3)With GIS interpolation technology,the inundation extents and depths of storm surge maps can be created from the simulated data to visualize and assess storm surge hazard levels including the lowest level,low level,high level,and the highest level.Then,the vulnerability assessment was made based on the land cover types in the coastal area of Huizhou.Eventually,combining hazard assessment with vulnerability assessment,the risk map during a typhoon with a specific return period in the study area was obtained.The results indicate that although 83.4%(227 km~2)of the total inundated area is a very high hazard zone to storm surge as the return period is the 1000-year,only 8%(21.97km~2)of the total inundated area is belonged to the very high risk zone to storm surge.For the other four typhoon scenarios,many inundated areas are at a high hazard level of storm surge(48.5%,53.0%,60.8%,67.3%),and but most of them change to moderate risk zones(64.9%,64.8%,68.4%,68.33%).It indicates that the area at a high hazard level cannot represent that area at a high-risk level due to the vulnerability levels of different land types.(4)The hazard of storm surge,the exposure of elements at risk,the physical vulnerability of elements at risk,and the social vulnerability taken into consideration,a comprehensive risk assessment model was constructed by integrating physical-vulnerability-based risk assessment and social-vulnerability-based risk assessment.In the aspect of physical-vulnerability-based risk assessment,GIS techniques and machine learning methods were utilized to extract the footprint of buildings.Moreover,in order to estimate physical damages to exposed elements,a database containing maximum damage values and depth–damage functions on a national scale,developed by Huizinga was adopted.In terms of social-vulnerability-based risk assessment,principal component analysis technology was used to establish an evaluation index system based on the society,economy,population,and social resilience.The physical-vulnerability-based risk assessment and the social-vulnerability-based risk assessment are added by weight to obtain the comprehensive risk assessment and zoning of storm surge in Daya Bay.The results show that the comprehensive risk level of storm surge disaster overall increases with the increasing typhoon intensity.The comprehensive risk level in coastal areas is higher than that in inland areas,and that in central and eastern coastal areas is higher than that in southwest coastal areas.The comprehensive risk of Xiayong village and the petrochemical industry zone in Daya Bay is significantly higher than that of other villages.In this paper,the proposed model taking the hazard of storm surge,the exposure of elements at risk,the physical vulnerability of elements at risk,and the social vulnerability into consideration was used to conduct the storm surge risk assessment case study of Daya Bay.It can not only address the questions in Chinese researches related to quantitative risk assessment of storm surge but also develop the theoretical foundation of storm surge risk management.In the case study,GIS techniques and machine learning methods were used to solve the problem of insufficient data for conducting quantitative risk assessment,and the risk zonation maps for sub-zones can help decision-makers recognize the areas that more likely to be heavily affected by the storm surge and allow them to develop evacuation strategies to minimize economic losses.Moreover,the procedure including typhoon scenario design,storm surge numerical simulation,physical-vulnerability-based risk assessment,social vulnerability-based risk assessment,comprehensive risk level zoning and assessment can be recommended as a guideline easily applied to other coastal cities that are usually affected by storm surge in China. |
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