【摘要】 近年来全球范围内频发的重大自然灾害事件,表明一种灾害引发一系列次生灾害的灾害链现象使得灾情通过累积放大效应而大大超过单一灾种灾情,深入研究灾害链灾情累积放大过程是有效防范巨灾风险的前提。首先,本文梳理了国内外研究中不同视角下对灾害链现象的理解,认为灾害链一般性概念中应当包含孕灾环境、致灾因子链、承灾体以及它们在时间和空间上复杂相互作用关系,只有从地理学的综合性角度出发,才能正确而完整的理解灾害链过程灾情累积放大机制。其次,按研究思路的差异,综述了当前研究灾害链灾情累积放大过程的5类方法,包括经验地学统计方法、概率模型、复杂网络模型、灾害模拟以及多学科理论方法。从描述灾害链要素在时间和空间上复合作用的角度出发,分别讨论了它们在刻画灾害链灾情放大过程中的优势与不足。选取了影响较大、灾害引发关系典型的地震灾害链与台风灾害链,从灾种维度综述上述几种方法在实际应用中的概况及进展。最后,提出综合多种方法发展与完善灾害链灾情累积放大效应过程的动态模拟是灾害链的研究趋势,其中关键在于模拟灾害链系统各要素的时间与空间上的耦合,研究思路从"静态—描述—解释"向"动态—过程—模拟"的转变是理解灾害链、灾害系统复杂性的重要途径。更多还原

【Abstract】 In recent years, the frequent catastrophic disasters have caused great losses of human lives and properties in the world. This indicates that disaster losses may be accumulated and amplified through disaster chains,in which one disaster triggers another, and so forth. The losses are much heavier in disaster chains than in a single disaster. Disaster chain is a typical complex form of regional disaster system. Understanding the amplification mechanisms of disaster chains is very important in catastrophe risk governance. This review first focuses on the concepts and understandings of disaster chain and summarizes a comprehensive definition from the geographic perspective through literature research. It is found that disaster chains have two common features, including the casualty relationship between different disasters and the spatial and temporal expansion of disaster losses. Only under a geographical framework, a sound and complete understanding of the disaster chain concept may be possible. A regional disaster system includes the environment, hazards, and exposure units and the complex spatial and temporal interactions of these elements. Second, considering the different research philosophies, five method categories in recently disaster chain research are summarized and analyzed. The five categories include empirical statistics methods, probabilistic models, complex network models, disaster system simulations, and multidisciplinary theories. The appropriateness and disadvantages of each category of methods are discussed with respect to their utility in describing disaster chain loss accumulation and amplification. Empirical statistics methods are a classical one that often use weighted average of a series of indicators. They have great advantage in taking into consideration various geographic factors and the modeling process is simple. But these methods cannot reveal the disaster chain evolution and processes. Probabilistic models can generate an overview of all possible events after a disaster have happened, as well as calculate the conditional probability. But they have the same problem as the statistics models. Disaster chain is a typical complex network. So the complex network theory may be used to describe the evolution of disaster chain networks. Such method should consider the spatial and temporal features of the disaster chain components in order to make the result more precise. Simulation methods are a promising one that can support the understanding of disaster chains dynamics, as well as the mechanism of the accumulation and amplification of disaster chain losses. However, simulation precision should be improved by including the spatial and temporal features of disaster chains in the future. Two types of important disaster chains, the seismic and typhoon disaster chains were used as examples to show the practical application of these methods. Finally, this review shows that the main trend of disaster chain research is to build and improve the dynamical model of disaster chain loss accumulation and amplification processes. The key is to connect all the factors spatially and temporally in a disaster chain system. It is necessary to transform the research approaches from "static-descriptive-explanatory" to "dynamic-process oriented-simulation" in order to understand the complexity of a disaster system.更多还原