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风暴洪水主要承灾体脆弱性分析——黄浦江案例

ISSN号：1000-0690
期刊名称：《地理科学》
时间：0
分类：X43[环境科学与工程—灾害防治]
作者机构：[1]浙江工商大学旅游与城市管理学院,浙江杭州310018, [2]上海师范大学地理系,上海200234, [3]拉夫堡大学地理系,莱斯特LE11 3TU, [4]华东师范大学地理系,上海200062
相关基金：国家自然科学基金面上项目（41071324）、国家自然科学基金重点项目（40730526）、教育部人文社会科学研究项目（12YJCZH257）、上海市教委重点学科项目（J50402）资助.

关键词：风暴洪水, 脆弱性, 黄浦江, storm induced flood, vulnerability, Huangpu River

中文摘要：

脆弱性分析是自然灾害风险研究的热点问题之一。风暴洪水是上海黄浦江流域所面临的最主要自然灾害类型,历史上对该区域造成极为严重的灾害损失。通过多次灾后调查,结合前人研究成果,构建该区域7种主要承灾体经济损失脆弱性方程和人口脆弱性方程。基于前期黄浦江风暴洪水多情景危险性成果,开展实证研究,结果显示：经济损失和人口脆弱性分布自黄浦江上游地区向下游逐渐降低。最后,提出未来脆弱性研究中有待进一步完善和发展的工作。

英文摘要：

Vulnerability analysis is one of the focuses in disaster risk research. However, so far, it is lack of common procedures and practices in China. Storm induced flooding, as one of the most devastating natural hazards in Huangpu river basin of Shanghai, causes considerable personal injury and property damage in the history. Vulnerabilities of economic loss and population were taken into consideration in this study, as the two factors were the most important flood affected areas. A land use map of Shanghai and a population distribution map of different districts of Shanghai in 2006 were generated as key inputs for vulnerability analysis. To per- form vulnerability analysis of economic loss, 7 vulnerability functions of different land uses （including residen- tial land, industrial land, traffic land, public service land, farm land, green land, and the others land uses） was constructed by combining the use of data questionnaires in a community-based field data collection campaign, and the integration of previous flood vulnerability research results. For population vulnerability analysis, Jonk- man＇ s population vulnerability function was employed as its representativeness and very little related data was available in Shanghai and all over China. Based on our previous results of multi-scenarios hazards analysis, a case study was presented to demonstrate the proposed algorithm. Subsequent analysis using Geographical In- formation Systems （GIS） was employed to illustrate the spatial and temporal distribution of vulnerability areas under different scenarios. The results indicated that （1） the vulnerability for economic loss and population grad- ually reduced from the upstream towards the downstream; （2） the vulnerability for economic loss and popula- tion increased with the increasing return periods; （3） the vulnerability for economic loss and population de- clines overland as distance increase of intrusion inland. Finally, some suggestions were presented for future re- searches.

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