灾害情景下城市脆弱性评估研究
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摘要
全球变暖,海平面上升,沿海城市自然灾害的暴露程度加剧,自然灾害的强度、频度和广度不断增长,以防范为目的的灾害风险评估显得格外重要。上世纪80年代灾害研究由致灾因子论向脆弱性研究转移,众多学者达成一致,脆弱性是理解灾难本质的前提,也是防灾减灾过程中人类可以有所作为的领域,自然致灾因子很难掌控,为降低灾情损失,减少承灾体脆弱性是最为直接和有效的方法。
在国家自然科学面上基金项目“中国沿海城市自然灾害风险评估体系研究”和国家自然科学重点基金项目“沿海城市自然灾害风险应急预案情景分析”的资助下,基于国际灾害风险科学发展的动向,架构自然灾害脆弱性分析的理论体系和程序方法,以上海为实证开展自然灾害脆弱性评估的研究,主要研究结果如下：
(1)“自然灾害系统中的脆弱性到底指什么?”围绕这一问题,本研究对自然灾害脆弱性的内涵、类别、结构等进行探讨,明确了敏感性、暴露性、恢复力的概念及其与脆弱性的相互关系,认清了脆弱性在灾难形成和减少风险中的决定性作用。自然灾害脆弱性不同于其它领域的脆弱性,城市自然灾害脆弱性的特征尤其独特。我们在理清自然灾害系统脆弱性的主要表现形式的基础上,着重对情景模拟下表征脆弱性的灾损曲线进行深入探讨。
(2)“如何评估自然灾害系统中的脆弱性?”在充分认识自然灾害脆弱性分析特点和困难的基础上,针对自然灾害领域几种经典的脆弱性分析模型,提出三种自然灾害脆弱性的评估方法,并在各种方法中,理顺了自然灾害脆弱性与风险的相互关系。三种脆弱性方法在实际应用中与评估区域空间尺度的大小密切相关。针对脆弱性目前研究的热点—脆弱性曲线,我们对其主要的构建方法进行了系统的归总,并对存在的主要问题及需要改进的方面进行了展望。
(3)上海地处东海之濒,人口与经济要素密集,不同类型的自然致灾和人为致灾因素相互作用,城市自然灾害事故呈现的显著特征包括：灾害类型多样,发生比较频繁；人为影响非常典型；灾情的放大作用较为明显；由于孕灾环境和灾害成因的复杂性,城市灾害链的综合效应越加突出。上海的灾害管理工作面临严峻考验：城市规模扩大,隐患也在增多；灾害防御的投入不足,需要加强;灾害综合管理水平不高;亟需加强城市防灾减灾科研,应急预案的实用性、可操作性与有效性亟待提高。
(4)上海市水灾系统风险识别显示出：台风、暴雨、过境洪水,是上海水灾的三种主要致灾因子,上海防汛墙的建设使潮灾和洪灾发生的频率明显减少,暴雨积水成为市区的主要水患；全球变暖、海平面上升和地面下沉是上海水灾频繁发生的背景,城市化导致的“热岛效应”、“雨岛效应”是灾害日益加重的原因,低洼地形、水利工程基础设施的不完善和灾害管理不到位,是上海水灾发生的根本原因,这些都是促进水灾产生的孕灾环境因素；上海水灾风险系统的承灾体中,农业首当其冲,另外,强暴雨带来的内涝灾害中,道路积水出现车辆抛锚、行人难以通行和居民居住建筑进水而产生的房屋结构及内部财产损失,尤其值得关注。
(5)农业的水灾脆弱性在沿海各省(市)均呈现增长的趋势；农业水灾脆弱性具有较强的区域分异规律,以15年平均水平相比,区域脆弱性大小顺序为：天津>河北>山东>浙江>辽宁>广西>上海>广东>福建>海南>江苏,北方农业的水灾脆弱性明显比南方大。另外,引入信息扩散的模糊数学方法,对沿海区域的农业水灾受灾率进行风险评估,水灾受灾风险大小排列的次序是：江苏>山东>天津>河北>辽宁>浙江>海南>广东>上海>广西>福建。这可以表明,上海市水灾脆弱性与风险的排序都较靠后,与同等空间尺度的另一直辖市—天津相比,天津的脆弱性和风险都比上海大,上海农业水灾脆弱性、风险都处于较低水平。将沿海各省(市)的农业水灾风险与脆弱性评估结果的次序进行对比,也反映减少脆弱性对降低灾害风险的重大意义。
(6)运用包络分析的CCR与BCC投入、产出模型,对上海各郊(县)的农业水灾脆弱性分异规律及其它特点进行了分析。其中,CCR模式显示,从时间尺度来看,上海郊区整体脆弱性状况由大到小的年份排序为：1991>1983>1984>1981>1985>1979>1986>1990>1980>1989>1987>1988；从空间尺度上,按照各个区域13年的效率平均值,区域农业水灾脆弱性由大到小排序为：南汇>金山>崇明>松江>宝山>青浦>浦东>嘉定>奉贤。而后,选用BCC模型进行技术脆弱性分析,求得规模脆弱值,并进行规模报酬分析,将9个区域划分为三类：嘉定、金山、松江、南汇和崇明五个区(县),无论从技术还是从规模上,都是水灾影响时农业脆弱性最大的区域；青浦区具有技术脆弱性但无规模脆弱性,脆弱性中等；宝山、浦东、奉贤区既无技术脆弱性也无规模脆弱性,脆弱性水平较低。依据此,探讨区域减少脆弱性的适宜播种规模。
(7)利用上海市防汛信息中心开发的暴雨内涝仿真模型,设置情景并对两种情景下的暴雨内涝进行了模拟,在此基础上,考虑内涝对道路产生的实际影响,根据水深划分级别,构造区域道路的暴露性评价模型,对中心城区各行政区进行实证研究,结果显示,二十年一遇暴雨情景下,中心城区各行政区的道路内涝暴露性排序为：徐汇>虹口>普陀>闸北>长宁>杨浦>黄浦>静安>卢湾；五十年一遇暴雨情景下,该排序为：徐汇>闸北>虹口>普陀>长宁>杨浦>黄浦>静安>卢湾。总体来说,中心城区的外围行政区道路的内涝暴露性较大,这与历史暴雨内涝的道路淹没状况基本一致。而后,仅仅使用五十年一遇的模拟情景,缩短空间尺度,以中心城区各街道为评估单位,按照相似的方法,对区域住宅的暴露性进行了分析,求得暴露性指数,并根据旧式住宅容易被淹及倒塌的事实,构造敏感性指数,对中心城区各街道住宅的脆弱性进行了评价,针对77个街道,据评价结果分析区域民居脆弱性产生的主要原因并进行分类。
(8)针对灾害主要承灾体、人类社会系统的核心—人群,在情景模拟的基础上,根据脆弱性概念及结构组成,强调人类自身抵御灾害的能力,选择代表性指标构建指标体系,客观赋予各指标权重、构造模型,进行徐汇五十年一遇暴雨内涝情景下的人群脆弱性评估。最终的评价结果显示：田林街道、凌云路街道、长桥街道、枫林路街道和漕河泾街道的人群脆弱性强;天平路街道、徐家汇街道和斜土路街道的人群脆弱性较强；虹梅路街道、康健新村街道、龙华街道和湖南路街道的人群脆弱性较弱；华泾镇是人群脆弱性最弱的地区。
(9)在对脆弱性曲线理论研究的基础上,借鉴国际脆弱性曲线建立的两种经典方法,结合上海实际,针对洪(潮)灾和暴雨内涝灾害,根据历史灾情和假设的水灾情景,首先,利用修正法,参照国内外的相关文献,构建不同土地利用类型的水灾脆弱性曲线,并利用ARCGIS进行空间展布,得到龙华镇三种水位时不同土地利用类型的脆弱性分布图。而后,在前人工作的基础上,对合成法做出三大方面的改进,构造不同收入阶层居住房屋结构及内部财产的脆弱性曲线,分别呈现为水深—单位面积损失曲线与水深—损失(损失率)曲线,并利用ARCGIS进行空间展布,得到龙华镇三种水位时居民建筑内部财产的脆弱性分布图,针对“麦莎”台风这一历史典型内涝情景中受影响较大的天平街道,也对其居民建筑结构的脆弱性进行空间展布,以求确定防灾减灾的重点区域和重点保护对象、为决策提供科学的依据。
综上所述,本研究在多学科交叉基础上,丰富、充实和发展城市灾害脆弱性评估的理论和方法体系,针对上海水灾的主要承灾体—农业、旧式民居、道路、人群、居住建筑及内部财产,基于灾害情景,利用经过改善的指标体系法、历史灾情的数理统计和脆弱性曲线三种方法,进行洪(潮)灾和暴雨内涝情形下不同空间尺度区域的承灾体脆弱性定量分析,多方法、多角度、多时空开展上海灾害脆弱性评估与区划研究,并建立灾害脆弱性评估的方法体系及程序规范。
自然灾害系统非常复杂,自然灾害脆弱性评估是一个涉及灾害学、风险学、地理学等多学科交叉的研究课题。本研究虽然在城市脆弱性评估和区划的研究上做了部分有益的探索,但相对于本研究领域科学理论的拓展和现实问题的解决还仅仅是一个开端。灾害脆弱性评估研究,还需在理论、方法和实践上做进一步深入细致的探讨。
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.
在国家自然科学面上基金项目“中国沿海城市自然灾害风险评估体系研究”和国家自然科学重点基金项目“沿海城市自然灾害风险应急预案情景分析”的资助下,基于国际灾害风险科学发展的动向,架构自然灾害脆弱性分析的理论体系和程序方法,以上海为实证开展自然灾害脆弱性评估的研究,主要研究结果如下：
(1)“自然灾害系统中的脆弱性到底指什么?”围绕这一问题,本研究对自然灾害脆弱性的内涵、类别、结构等进行探讨,明确了敏感性、暴露性、恢复力的概念及其与脆弱性的相互关系,认清了脆弱性在灾难形成和减少风险中的决定性作用。自然灾害脆弱性不同于其它领域的脆弱性,城市自然灾害脆弱性的特征尤其独特。我们在理清自然灾害系统脆弱性的主要表现形式的基础上,着重对情景模拟下表征脆弱性的灾损曲线进行深入探讨。
(2)“如何评估自然灾害系统中的脆弱性?”在充分认识自然灾害脆弱性分析特点和困难的基础上,针对自然灾害领域几种经典的脆弱性分析模型,提出三种自然灾害脆弱性的评估方法,并在各种方法中,理顺了自然灾害脆弱性与风险的相互关系。三种脆弱性方法在实际应用中与评估区域空间尺度的大小密切相关。针对脆弱性目前研究的热点—脆弱性曲线,我们对其主要的构建方法进行了系统的归总,并对存在的主要问题及需要改进的方面进行了展望。
(3)上海地处东海之濒,人口与经济要素密集,不同类型的自然致灾和人为致灾因素相互作用,城市自然灾害事故呈现的显著特征包括：灾害类型多样,发生比较频繁；人为影响非常典型；灾情的放大作用较为明显；由于孕灾环境和灾害成因的复杂性,城市灾害链的综合效应越加突出。上海的灾害管理工作面临严峻考验：城市规模扩大,隐患也在增多；灾害防御的投入不足,需要加强;灾害综合管理水平不高;亟需加强城市防灾减灾科研,应急预案的实用性、可操作性与有效性亟待提高。
(4)上海市水灾系统风险识别显示出：台风、暴雨、过境洪水,是上海水灾的三种主要致灾因子,上海防汛墙的建设使潮灾和洪灾发生的频率明显减少,暴雨积水成为市区的主要水患；全球变暖、海平面上升和地面下沉是上海水灾频繁发生的背景,城市化导致的“热岛效应”、“雨岛效应”是灾害日益加重的原因,低洼地形、水利工程基础设施的不完善和灾害管理不到位,是上海水灾发生的根本原因,这些都是促进水灾产生的孕灾环境因素；上海水灾风险系统的承灾体中,农业首当其冲,另外,强暴雨带来的内涝灾害中,道路积水出现车辆抛锚、行人难以通行和居民居住建筑进水而产生的房屋结构及内部财产损失,尤其值得关注。
(5)农业的水灾脆弱性在沿海各省(市)均呈现增长的趋势；农业水灾脆弱性具有较强的区域分异规律,以15年平均水平相比,区域脆弱性大小顺序为：天津>河北>山东>浙江>辽宁>广西>上海>广东>福建>海南>江苏,北方农业的水灾脆弱性明显比南方大。另外,引入信息扩散的模糊数学方法,对沿海区域的农业水灾受灾率进行风险评估,水灾受灾风险大小排列的次序是：江苏>山东>天津>河北>辽宁>浙江>海南>广东>上海>广西>福建。这可以表明,上海市水灾脆弱性与风险的排序都较靠后,与同等空间尺度的另一直辖市—天津相比,天津的脆弱性和风险都比上海大,上海农业水灾脆弱性、风险都处于较低水平。将沿海各省(市)的农业水灾风险与脆弱性评估结果的次序进行对比,也反映减少脆弱性对降低灾害风险的重大意义。
(6)运用包络分析的CCR与BCC投入、产出模型,对上海各郊(县)的农业水灾脆弱性分异规律及其它特点进行了分析。其中,CCR模式显示,从时间尺度来看,上海郊区整体脆弱性状况由大到小的年份排序为：1991>1983>1984>1981>1985>1979>1986>1990>1980>1989>1987>1988；从空间尺度上,按照各个区域13年的效率平均值,区域农业水灾脆弱性由大到小排序为：南汇>金山>崇明>松江>宝山>青浦>浦东>嘉定>奉贤。而后,选用BCC模型进行技术脆弱性分析,求得规模脆弱值,并进行规模报酬分析,将9个区域划分为三类：嘉定、金山、松江、南汇和崇明五个区(县),无论从技术还是从规模上,都是水灾影响时农业脆弱性最大的区域；青浦区具有技术脆弱性但无规模脆弱性,脆弱性中等；宝山、浦东、奉贤区既无技术脆弱性也无规模脆弱性,脆弱性水平较低。依据此,探讨区域减少脆弱性的适宜播种规模。
(7)利用上海市防汛信息中心开发的暴雨内涝仿真模型,设置情景并对两种情景下的暴雨内涝进行了模拟,在此基础上,考虑内涝对道路产生的实际影响,根据水深划分级别,构造区域道路的暴露性评价模型,对中心城区各行政区进行实证研究,结果显示,二十年一遇暴雨情景下,中心城区各行政区的道路内涝暴露性排序为：徐汇>虹口>普陀>闸北>长宁>杨浦>黄浦>静安>卢湾；五十年一遇暴雨情景下,该排序为：徐汇>闸北>虹口>普陀>长宁>杨浦>黄浦>静安>卢湾。总体来说,中心城区的外围行政区道路的内涝暴露性较大,这与历史暴雨内涝的道路淹没状况基本一致。而后,仅仅使用五十年一遇的模拟情景,缩短空间尺度,以中心城区各街道为评估单位,按照相似的方法,对区域住宅的暴露性进行了分析,求得暴露性指数,并根据旧式住宅容易被淹及倒塌的事实,构造敏感性指数,对中心城区各街道住宅的脆弱性进行了评价,针对77个街道,据评价结果分析区域民居脆弱性产生的主要原因并进行分类。
(8)针对灾害主要承灾体、人类社会系统的核心—人群,在情景模拟的基础上,根据脆弱性概念及结构组成,强调人类自身抵御灾害的能力,选择代表性指标构建指标体系,客观赋予各指标权重、构造模型,进行徐汇五十年一遇暴雨内涝情景下的人群脆弱性评估。最终的评价结果显示：田林街道、凌云路街道、长桥街道、枫林路街道和漕河泾街道的人群脆弱性强;天平路街道、徐家汇街道和斜土路街道的人群脆弱性较强；虹梅路街道、康健新村街道、龙华街道和湖南路街道的人群脆弱性较弱；华泾镇是人群脆弱性最弱的地区。
(9)在对脆弱性曲线理论研究的基础上,借鉴国际脆弱性曲线建立的两种经典方法,结合上海实际,针对洪(潮)灾和暴雨内涝灾害,根据历史灾情和假设的水灾情景,首先,利用修正法,参照国内外的相关文献,构建不同土地利用类型的水灾脆弱性曲线,并利用ARCGIS进行空间展布,得到龙华镇三种水位时不同土地利用类型的脆弱性分布图。而后,在前人工作的基础上,对合成法做出三大方面的改进,构造不同收入阶层居住房屋结构及内部财产的脆弱性曲线,分别呈现为水深—单位面积损失曲线与水深—损失(损失率)曲线,并利用ARCGIS进行空间展布,得到龙华镇三种水位时居民建筑内部财产的脆弱性分布图,针对“麦莎”台风这一历史典型内涝情景中受影响较大的天平街道,也对其居民建筑结构的脆弱性进行空间展布,以求确定防灾减灾的重点区域和重点保护对象、为决策提供科学的依据。
综上所述,本研究在多学科交叉基础上,丰富、充实和发展城市灾害脆弱性评估的理论和方法体系,针对上海水灾的主要承灾体—农业、旧式民居、道路、人群、居住建筑及内部财产,基于灾害情景,利用经过改善的指标体系法、历史灾情的数理统计和脆弱性曲线三种方法,进行洪(潮)灾和暴雨内涝情形下不同空间尺度区域的承灾体脆弱性定量分析,多方法、多角度、多时空开展上海灾害脆弱性评估与区划研究,并建立灾害脆弱性评估的方法体系及程序规范。
自然灾害系统非常复杂,自然灾害脆弱性评估是一个涉及灾害学、风险学、地理学等多学科交叉的研究课题。本研究虽然在城市脆弱性评估和区划的研究上做了部分有益的探索,但相对于本研究领域科学理论的拓展和现实问题的解决还仅仅是一个开端。灾害脆弱性评估研究,还需在理论、方法和实践上做进一步深入细致的探讨。
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.
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