经常性热带洪水灾害背景下两种生计脆弱性指数的绩效措施比较

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摘要

自然灾害通常会造成相当大的社会脆弱性,这种脆弱性是暴露、敏感性和适应性的函数。生计脆弱性评估(LVA)有利于具体地点的抗灾能力建设和灾害管理。目前有两种流行的生计脆弱性评估指数--(1)政府间气候变化专门委员会(IPCC,2007 年)的生计脆弱性指数(LVI)和(2)Hahn 等人(2009 年)的另一种方法。本研究旨在揭示更适合解决印度马尤拉克希河流域农村社区由洪水引发的生计脆弱性问题的指数。为此,主要根据对五个社区发展(C.D.)区块 43 个村庄 2382 户家庭进行问卷调查所收集的原始数据,对涉及 35 个参数的暴露性质、适应能力和敏感性进行了测量。此外,还使用了年度洪水报告、地区人口普查报告、地形图和卫星图像作为辅助数据。结果显示,根据 Hahn 等人的 LVI 值,Khargram(LVI- 0.41)是最脆弱的区块,而 Nabagram(LVI- 0.35)是最不脆弱的区块。然而,根据 IPCC LVI,Bharatpur-I 的 LVI 值最高(0.02),Burwan 的 LVI 值最低(-0.09)。据观察,暴露程度与 IPCC-LVI 呈强烈的正相关,而适应能力与 Hahn 等人的 LVI 也保持着类似的相关性。有趣的是,Kandi 是暴露程度最高的区块(得分:0.59),但适应能力较强(得分:0.47),因此被排除在两种方法的高 LVI 类别之外。这种性能比较评估强调了决策者在制定微观灾害管理计划前所做工作的重要性。
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A comparison of performance measures of two livelihood vulnerability indices in the context of recurrent tropical flood hazards

Natural hazards often pose a considerable amount of social vulnerability which is the function of exposure, sensitivity and adaptation. Livelihood vulnerability assessment (LVA) benefits site-specific resilience building and disaster management. There are two popular indices of LVA – (1) the livelihood vulnerability index (LVI) of the Intergovernmental Panel on Climate Change (IPCC, 2007) and another method by (2) Hahn et al. (2009). The study intends to reveal the index that is more suitable to address the flood-induced livelihood vulnerability of the rural communities of the Mayurakshi river basin, India. To this end, the nature of exposure, adaptive capacity and sensitivity involving 35 parameters are measured mainly based on the primary data collected from a questionnaire survey executed over 2382 households spreading over 43 villages from five community development (C.D.) blocks. Moreover, the annual flood reports, district census reports, topographical maps, and satellite images are used as secondary data. The result shows that as per Hahn et al.’s LVI, Khargram (LVI- 0.41) is the most vulnerable block while Nabagram (LVI- 0.35) is the least vulnerable block. However, according to IPCC-LVI, Bharatpur-I has the highest LVI (0.02) and Burwan has the lowest LVI (-0.09). It is observed that exposure exhibits a strong positive correlation with IPCC-LVI and adaptive capacity also maintains a similar correlation with Hahn et al.’s LVI. Interestingly, Kandi is the most exposed block (score: 0.59) with a high adaptive capacity (score: 0.47) resulting in its exclusion from the high LVI category of both methods. This comparative performance assessment underscores the significance of the work before the decision-makers in preparing microscale disaster management plans.

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