Research On Vulnerability Assessment Of Cities On The Disaster Scenario

Owing to the global warming and sea-level rising, the effect of natural disasters on coastal cities is becoming more and more obvious. The intensity, frequency and extent of sudden-onset natural hazards increase constantly, so the risk assessment of disasters for the purpose of preventing happening is becoming especially important. In 1980s, the focus of research transferred from the potential hazard factor to vulnerability, on which many scholars have reached a consensus. They all think that vulnerability is the premise to understand the essence of disasters, and the field in which people can do something to make a difference in disaster prevention and mitigation. The hazard factors are difficult to control. Therefore, to decrease the vulnerability is the most effective method to reduce the losses caused by disasters.Supported by the Foundation of National Natural Science of China "Study on Natural Disasters Risk Assessment System in Chinese Coastal Cities" and"Scenario Analysis of Emergency Responses to Natural Disasters Risk in Coastal Cities", and based on the development of the international disaster risk science and the theory system and program to guide the vulnerability research about natural disasters, here a lot of researches on vulnerability with Shanghai as an example have been done. The research findings are as follows:(1)What on earth means the vulnerability in the natural disaster system? Around this issue, the research discussed the content, type and structure of vulnerability. We defined the concept of sensitivity, exposure, resilience and found out the difference and relationship among them. Vulnerability plays a decisive role during the formation of disasters. It is of great significance to reduce disaster risk by controlling vulnerability. Vulnerability is distinctive in the field of disaster research in cities. After recognizing main formations of vulnerability in different methods, we put our emphasis on "vulnerability curve". We tried to focus on the function of it in risk assessment based on the method of scenario simulation.(2)How to evaluate the vulnerability in the natural disaster system? After recognizing the characteristics and difficulty to assess the vulnerability in natural disasters, based on several classic models, we brought forward three main methods to assess vulnerability in natural disasters. In each method, risk and vulnerability have a close relationship. In practice, the choose of assess methods relies on the spatial scale of the study area. About the hot subject of research-vulnerability curve, we summarized the methods to built it and proposed some advice to improve them.(3) Shanghai is close to the East China Sea. For the reason that Shanghai is densely populated and an economic center, different kinds of natural hazard factors and anthropic factors interact and affect each other. The typical characteristics of urban natural disasters are:diverse disaster types, frequent occurring, obvious anthropic factors, amplified influence of disasters, the complexity of environment susceptible to disasters and causes of disasters, and the more and more distinct synthetic effect of urban hazard chains. Shanghai never experienced serious disasters, so the Shanghai government faces a big test of disaster management. With the expense of city size, the hazard is becoming more; the invest in defending disasters is not enough and needs to be strengthened; the comprehensive disaster management is relatively low; and researches on how to prevent and reduce the happening of urban disasters starve for more support for lack of practical, operable, and effective scheme.(4)Shanghai flood system risk identification shows:typhoon, rainstorm, and flood are three factors to cause hazards; The flood-controlling wall reduces the occurring frequency of surge disasters and floods, and the rainstorm waterlogging becomes the main danger; the global warming, sea-level rising and land subsidence are the background of Shanghai frequent flood disasters; thermal island effect and rain island effect due to urbanization are the main reasons for increasingly serious hazards; low-lying terrain, imperfect hydraulic infrastructure, and improper disaster management are basic reasons for Shanghai flood. In Shanghai, agriculture is the first to be considered during floods. What's more, when hard rainstorms happen, waterlogging would lead to the result that vehicle broke down and people were difficult to walk, and drowned houses suffered heavy losses.(5) Flood vulnerability presents an increasing trend in costal cities; Flood vulnerability has a strong regional differentiation, take the 15-year average comparison as an example, the order of regional vulnerability is:Tianjin> Hebei> Shandong> Zhejiang> Liaoning> Guangxi> Shanghai> Guangdong> Fujian> Hainan> Jiangsu; the vulnerability in the north is more obvious than that in the south. In addition, according to fuzzy mathematics with the introduction of information diffusion, we made a risk assessment to the affected rate of coastal areas, and the descending order of flood risk is:Jiangsu> Shandong> Tianjin> Hebei> Liaoning> Zhejiang> Hainan> Guangdong> Shanghai> Guangxi> Fujian. The results show that Shanghai flood vulnerability and risk ranking are both near the end on the list. Shanghai agricultural flood vulnerability and risk are in lower level. Compared with another municipality in the same spatial scale - Tianjin, Shanghai has less vulnerability than Tianjin. The contrast of disaster risk and vulnerability results reflects that to bring down vulnerability is of great significance to reduce disaster risk.(6) We made analysis of flood vulnerability variation and other characteristics of agriculture in the suburban counties of Shanghai by using CCR and BCC input and output models with data envelopment analysis. In the research, CCR model shows that the overall vulnerability of Shanghai suburbs in descending order from the time scale appears:1991> 1983> 1984> 1981> 1985> 1979> 1986> 1990> 1980> 1989> 1987> 1988; In terms of space scale, according to the 13-year efficiency average of each region, the descending order of flood vulnerability is:Nanhui> Jinshan> Chongming> Matsue> Golconda> Qingpu> Pudong> Jiading> Fengxian. Then, we used BCC model to make a technical vulnerability analysis, got vulnerability scale values and conducted scale analysis. The nine regions can be divided into three categories:as for the five counties, Jiading, Jinshan, Songjiang, Nanhui and Chongming, no matter in terms of technique or scale, the vulnerability to floods is the largest; Qingpu District is of technical vulnerability, but without scale vulnerability, and the scale vulnerability is medium; Baoshan, Pudong, and Fengxian District are neither of technical vulnerability nor of scale vulnerability. Accordingly, it's proper to study suitable planting size to reduce region vulnerability.(7)Using the simulation model of rainstorm waterlogging developed by the Shanghai Flood-Control Information Center, we set the scenarios and simulated waterlogging in two kinds of rainstorm. On this base, we took the actual impact of waterlogging on roads into consideration, defined the exposure rating according to water depth, built an exposure evaluation model of regional roads, and did empirical research in downtown areas. The research results show that in the 20-year return period storm scenario, waterlogging exposure order of roads in downtown administrative areas is:Xuhui> Hongkou> Putuo> Zhabei> Changning> Yangpu> Huangpu> Jing'an> Luwan; while in the 50-year return period storm scenario, the order is:Xuhui> Zhabei> Hongkou> Putuo> Changning> Yangpu> Huangpu> Jing'an> Luwan. Generally speaking, the outside administrative roads in downtown areas have greater exposure to waterlogging, which is in compliance with road flooded conditions in historical rainstorm waterlogging. Later, only using the 50-year return period storm scenario with spatial scale cut down, and taking the streets in downtown areas as the assessment units, we made an analysis about the exposure of regional residences and got the exposure index according to a similar method. We also built a sensibility index in the light of the fact that old residences are prone to flood, and made an assessment on the vulnerability of residences in downtown streets. On the basis of assessment results, we generalized main causes for downtown regional residence vulnerability and classified them into different categories.(8) Since people are the main suffering body affected by disasters and the core of the human social system. Based on scenario simulation and in connect with vulnerability concept and structure, human capability to resist disasters was considered. We selected representative indicators to build indicator system, objectively endowed them with weight, built a model, and made population vulnerability assessment in Xuhui District with the 50-year return period waterlogging. The final assessment results tell:population vulnerability of Tianlin Street, Lingyun Street, Changqiao Street, Fenglin Street, and Caohejing Street is most obvious; that of Tianping Street, Xujiahui Street, and Xietulu Street is medium; that of Hongmei Road Street, Healthy Village Street, Longhua Street and Hunan Road Street is weak; Huajing Town is the area with the weakest population vulnerability.(9) On the basis of the vulnerability curve theory study, we borrowed two classical methods of vulnerability established at home and abroad. Directing at flood (tidal) and waterlogging disasters, historical disaster and assumptions for flood scenarios, first of all, we implied the revised method, in the light of literature domestic and abroad to build different vulnerability curves for different types of land; and carried out spatial distribution by using ARCGIS, and got vulnerability distribution map of different types of land use in three water levels. Then, on the basis of previous work, as for the loss curve constructed with the synthesis method, we made the following three improvements:to construct the vulnerability curve of residence structure and property in house in allusion to different income groups, to present the depth-loss per unit area curve and the depth-loss (loss rate) curve respectively. Using GIS to make spatial distribution, we got the vulnerability distribution map of residence structure and property in house in three water levels in Longhua town and carried out vulnerability special spreading in Tianping Street which suffered from "Matsa" the most, the typical waterlogging disaster scenario in history, to make sure key areas and main objects of protection, to provide scientific basis for decision-making, and to achieve sustainable development of cities.In sum, on the base of multidisciplinary, in direct at main suffering bodies of Shanghai flood including agriculture, old houses, roads, people, and resident buildings and properties, this dissertation intends to enrich and develop urban disaster vulnerability assessment theory and method system and makes a vulnerability quantitative analysis of suffering bodies in different regional scales under the influence of flood and rainstorm waterlogging by using an improved indicators system, the mathematical statistics of historical disasters and vulnerability curves based on disaster scenario. The author makes vulnerability assessment research and zoning study from multi-angle, in different times and using three methods, and establishes disaster vulnerability analysis method system and process specification.Natural disaster system is quite complex. Vulnerability assessment is a multidisciplinary study subject involving science of disaster, hazard, and geography. This dissertation gets some useful conclusion by probing to the research into the urban vulnerability assessment and zoning, however, it is a beginning in this research field of scientific theory expanding and real problem resolving. The vulnerability assessment research needs deep probe and detailed discussion in theory, methods and practice.