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A relative vulnerability estimation of flood disaster using data envelopment analysis in the Dongting Lake region of Hunan

机译：基于数据包络分析的湖南洞庭湖区洪水灾害相对脆弱性估算。

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The vulnerability to flood disaster is addressed by a number of studies. It is of great importance to analyze the vulnerability of different regions and various periods to enable the government to make policies for distributing relief funds and help the regions to improve their capabilities against disasters, yet a recognized paradigm for such studies seems missing. Vulnerability is defined and evaluated through either physical or economic-ecological perspectives depending on the field of the researcher concerned. The vulnerability, however, is the core of both systems as it entails systematic descriptions of flood severities or disaster management units. The research mentioned often has a development perspective, and in this article we decompose the overall flood system into several factors: disaster driver, disaster environment, disaster bearer, and disaster intensity, and take the interaction mechanism among all factors as an indispensable function. The conditions of flood disaster components are demonstrated with disaster driver risk level, disaster environment stability level and disaster bearer sensitivity, respectively. The flood system vulnerability is expressed as vulnerability Combining double low line f(risk, stability, sensitivity). Based on the theory, data envelopment analysis method (DEA) is used to detail the relative vulnerability's spatiotemporal variation of a flood disaster system and its components in the Dongting Lake region. The study finds that although a flood disaster system's relative vulnerability is closely associated with its components' conditions, the flood system and its components have a different vulnerability level. The overall vulnerability is not the aggregation of its components' vulnerability. On a spatial scale, zones central and adjacent to Dongting Lake and/or river zones are characterized with very high vulnerability. Zones with low and very low vulnerability are mainly distributed in the periphery of the Dongting Lake region. On a temporal scale, the occurrence of a vibrating flood vulnerability trend is observed. A different picture is displayed with the disaster driver risk level, disaster environment stability level and disaster bearer sensitivity level. The flood relative vulnerability estimation method based on DEA is characteristic of good comparability, which takes the relative efficiency of disaster system input-output into account, and portrays a very diverse but consistent picture with varying time steps. Therefore, among different spatial and time domains, we could compare the disaster situations with what was reflected by the same disaster. Additionally, the method overcomes the subjectivity of a comprehensive flood index caused by using an a priori weighting system, which exists in disaster vulnerability estimation of current disasters.
机译：许多研究解决了洪水灾害的脆弱性。分析不同地区和不同时期的脆弱性，以使政府能够制定分配救灾资金的政策，并帮助各地区提高抗灾能力，具有十分重要的意义，但似乎缺少此类研究的公认范式。根据研究人员的领域，从物理或经济生态角度定义和评估漏洞。但是，该漏洞是这两个系统的核心，因为它需要对洪水严重性或灾难管理单位进行系统的描述。提到的研究通常具有发展前景，在本文中，我们将整个洪水系统分解为几个因素：灾害驱动因素，灾害环境，灾害承担者和灾害强度，并将所有因素之间的相互作用机制作为必不可少的功能。分别以灾害驾驶员风险等级，灾害环境稳定等级和灾害承担者敏感性来证明洪水灾害组成部分的状况。洪水系统的脆弱性表示为结合了双重低线 f 的脆弱性（风险，稳定性，敏感性）。基于该理论，采用数据包络分析法（DEA）详细描述了洞庭湖区洪灾灾害系统及其组成部分的相对脆弱性时空变化。 该研究发现，尽管洪水灾害系统的相对脆弱性与其组成部分的状况密切相关，但洪水系统及其组成部分具有不同的脆弱性级别。整体漏洞不是其组件漏洞的汇总。在空间尺度上，洞庭湖和/或河区的中心和相邻区域具有很高的脆弱性。脆弱性极低的区域主要分布在洞庭湖地区的外围。在时间尺度上，观察到振动洪水易损性趋势的发生。灾难驱动程序风险级别，灾难环境稳定级别和灾难承载者敏感级别显示不同的图片。 基于DEA的洪水相对脆弱性估计方法具有可比性好的特点，它考虑了灾害系统投入产出的相对效率，并描绘了一个非常多样化但始终如一的图，其时变是不同的。因此，在不同的时空域中，我们可以将灾难情况与同一场灾难所反映的情况进行比较。另外，该方法克服了由于使用先验加权系统而导致的综合洪水指数的主观性，该先验加权系统存在于当前灾害的灾害易损性估计中。

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