4.6 Article

Community-based scenario modelling and disaster risk assessment of urban rainstorm waterlogging

期刊

JOURNAL OF GEOGRAPHICAL SCIENCES
卷 21, 期 2, 页码 274-284

出版社

SCIENCE PRESS
DOI: 10.1007/s11442-011-0844-7

关键词

scenario modelling; small-scale; rainstorm waterlogging; disaster risk assessment; Shanghai

资金

  1. National Nature Science Foundation of China [41071324, 40730526]
  2. Shanghai Municipal Education Commission [J50402]
  3. Science and Technology Commission of Shanghai Municipality [08240514000]
  4. Shanghai Normal University [DZL809]

向作者/读者索取更多资源

Scenario modelling and the risk assessment of natural disasters is one of the hotspots in disaster research. However, up until now, urban natural disaster risk assessments lack common procedures and programmes. This paper selects rainstorm waterlogging as a disaster to research, which is one of the most frequently occurring hazards for most cities in China. As an example, we used a small-scale integrated methodology to assess risks relating to rainstorm waterlogging hazards in the Jing'an District of Shanghai. Based on the basic concept of disaster risk, this paper applies scenario modelling to express the risk of small-scale urban rainstorm waterlogging disasters in different return periods. Through this analysis of vulnerability and exposure, we simulate different disaster scenarios and propose a comprehensive analysis method and procedure for small-scale urban storm waterlogging disaster risk assessments. A grid-based Geographical Information System (GIS) approach, including an urban terrain model, an urban rainfall model and an urban drainage model, was applied to simulate inundation area and depth. Stage-damage curves for residential buildings and contents were then generated by the loss data of waterlogging from field surveys, which were further applied to analyse vulnerability, exposure and loss assessment. Finally, the exceedance probability curve for disaster damage was constructed using the damage of each simulated event and the respective exceedance probabilities. A framework was also developed for coupling the waterlogging risk with the risk planning and management through the exceedance probability curve and annual average waterlogging loss. This is a new exploration for small-scale urban natural disaster scenario simulation and risk assessment.

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