灾害链风险评估的概念模型——以汶川5·12特大地震为例

doi:10.11820/dlkxjz.2013.01.014

摘要/Abstract

摘要： 大量事实表明,每发生一种重大灾害总会诱发一系列次生灾害,形成破坏力远超单一灾种的灾害链现象。要有效防范灾害链风险,理清其形成过程、构建其评估模型是前提。在梳理国内外链式风险评估概念模型的基础上,结合“5·12”汶川特大地震灾害链案例,初步提出灾害链风险评估的概念模型。①孕灾环境敏感性是致灾因子链发的重要影响因素,决定灾害链风险的链发概率,确定影响孕灾环境敏感性的因素及定量关系是评估关键;②灾害链中承灾体重复受灾导致脆弱性增大,脆弱性变化评估的引入将提高灾害链风险评估结果的精度。本文旨在为完善区域灾害系统理论,进一步推动灾害链风险防范提供依据。

关键词: 风险评估, 概念模型, 汶川地震, 灾害链

Abstract: A vast number of cases have demonstrated that a major disaster can trigger a series of secondary disasters, forming a disaster chain with much more destructive power than a single-type disaster. Understanding the process of disaster chain formation and establishing a conceptual model for risk assessment are the premise for governance of the disaster chain risk. In this paper, we first reviewed the chain risk assessment models from the studies at home and abroad, e.g., the accident chain, supply chain and so on, and then, taking Wenchuan Earthquake as a case study, we proposed a new conceptual model of disaster chain risk assessment. The two major conclusions are: (1) sensitivity of the environment susceptible to disasters is an important impact factor, which determines the probability of disaster chain. Therefore, the key aspect of risk assessment is to identify the factors affecting the sensitivity of the environment and characterize their quantitative relationships. (2) Vulnerability of a disaster-affected area in a disaster chain increases after incurring repeated hazards; evaluation of change of the vulnerability of the area will improve the precision of disaster chain risk assessment. This study aims to improve the theory on disaster system research and provide a basis for further improvement of disaster chain risk governance.

Key words: conceptual model, disaster chain, risk assessment, Wenchuan Earthquake

张卫星, 周洪建. 灾害链风险评估的概念模型——以汶川5·12特大地震为例[J]. 地理科学进展, 2013, 32(1): 130-144.

ZHANG Weixing, ZHOU Hongjian. Conceptual model of disaster chain risk assessment: Taking Wenchuan Earthquake on 12 May 2008 as a case[J]. PROGRESS IN GEOGRAPHY, 2013, 32(1): 130-144.

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