Quantitative Evaluation of Flood Control Measures and Educational Support to Reduce Disaster Vulnerability of the Poor Based on Household-level Savings Estimates
Quantitative Evaluation of Flood Control Measures and Educational Support to Reduce Disaster Vulnerability of the Poor Based on Household-level Savings Estimates
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基于家庭储蓄估算的防洪措施和教育支持的定量评估，以减少贫困人口的灾害脆弱性
DOI：
10.1007/s41885-022-00112-y
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Kawasaki Akiyuki
中科院分区：
文献类型：
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作者：
Nakamura Risa;Kawasaki Akiyuki
在发展中国家，由于预算限制，难以对减少灾害风险进行投资，灾害使贫穷陷阱更加恶化。为了通过减少灾害风险来减轻贫穷，不仅应考虑灾害的直接直接影响，还应考虑其长期和间接影响。然而，由于往往根据减少损害的程度来评估各项政策的效果，因此对穷人的影响通常被忽视，因为穷人资产很少，损失也较小。在这里，我们的目的是定量评估防洪措施和教育支持的影响，在家庭层面上的贫困人口的洪水脆弱性。我们构建了一个模型来计算单个家庭的储蓄，并使用洪水损失与储蓄的比率来确定他们的洪水脆弱性。接下来，我们估计了各种政策降低洪水脆弱性的程度。我们发现，教育支持是合适的，以减少穷人的洪水脆弱性具有成本效益，特别是当预算很小。基尼系数的预测证实，教育支助在减少收入不平等方面是有效的。这项研究的新奇之处在于，它定量地将洪水损失、储蓄和教育联系起来，这些都是影响穷人洪水脆弱性的因素，它比较了各种防洪措施和教育支持在家庭一级对洪水脆弱性的影响。虽然该模式是利用缅甸巴戈的住户调查数据制定的，但该框架也应适用于其他区域。
In developing countries, where budget constraints make it difficult to invest in disaster risk reduction, disasters worsen the poverty trap. To alleviate poverty by reducing the risk of disasters, not only the immediate direct impacts of disasters but also their long-term and indirect impacts should be considered. However, since the effects of individual policies are often evaluated based on the extent of damage reduction, the impact on the poor, who have few assets and thus small losses, is generally ignored. Here, we aimed to quantitatively evaluate the effects of flood control measures and educational support in terms of the flood vulnerability of the poor at the household level. We constructed a model to calculate the savings of individual households and used the flood damage-to-savings ratio to determine their flood vulnerability. Next, we estimated the extent to which the flood vulnerability is reduced by various policies. We found that educational support is suitable for reducing the flood vulnerability of the poor cost-effectively, especially when the budgets are small. Gini coefficient predictions confirmed that educational support is effective in reducing income inequality. The novelty of this study is that it quantitatively links flood damage, savings, and education, which are factors that affect the flood vulnerability of the poor, and it compares the effects of various flood control measures and educational support at the household level in terms of the flood vulnerability. While the model was developed using household survey data from Bago, Myanmar, the framework should be applicable to other regions as well.