A vulnerability curve is an important tool for the rapid assessment of drought losses, and it can provide a scientific basis for drought risk prevention and post-disaster relief. Those populations with difficulty in accessing drinking water because of drought (hereon “drought at risk populations”, abbreviated as DRP) were selected as the target of the analysis, which examined factors contributing to their risk status. Here, after the standardization of disaster data from the middle and lower reaches of the Yangtze River in 2013, the parameter estimation method was used to determine the probability distribution of drought perturbations data. The results showed that, at the significant level of α = 0.05, the DRP followed the Weibull distribution, whose parameters were optimal. According to the statistical characteristics of the probability density function and cumulative distribution function, the bulk of the standardized DRP is concentrated in the range of 0 to 0.2, with a cumulative probability of about 75%, of which 17% is the cumulative probability from 0.2 to 0.4, and that greater than 0.4 amounts to only 8%. From the perspective of the vulnerability curve, when the variance ratio of the normalized vegetation index (NDVI) is between 0.65 and 0.85, the DRP will increase at a faster rate; when it is greater than 0.85, the growth rate of DRP will be relatively slow, and the disaster losses will stabilize. When the variance ratio of the enhanced vegetation index (EVI) is between 0.5 and 0.85, the growth rate of DRP accelerates, but when it is greater than 0.85, the disaster losses tend to stabilize. By comparing the coefficient of determination (R²) values fitted for the vulnerability curve, in the same situation, EVI is more suitable to indicate drought vulnerability than NDVI for estimating the DRP.

中文翻译：

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基于遥感指数的干旱脆弱性分析

脆弱性曲线是快速评估干旱损失的重要工具，可以为预防干旱风险和灾后救济提供科学依据。选择那些由于干旱而难以获得饮用水的人口（以下简称“处于危险中的人口”，简称为DRP）作为分析的目标，分析了造成其危险状况的因素。这里，在2013年对长江中下游地区的灾害数据进行标准化之后，使用参数估计方法确定干旱扰动数据的概率分布。结果表明，在α= 0.05的显着水平下，DRP遵循Weibull分布，其参数是最佳的。根据概率密度函数和累积分布函数的统计特性，标准化DRP的大部分集中在0到0.2的范围内，累积概率约为75％，其中17％是0.2的累积概率。到0.4，而大于0.4则只有8％。从脆弱性曲线的角度来看，当归一化植被指数（NDVI）的方差比在0.65和0.85之间时，DRP将以更快的速度增加；当大于0.85时，DRP的增长率将相对缓慢，灾难损失将保持稳定。当增强植被指数（EVI）的方差比在0.5和0.85之间时，DRP的增长率加快，但是当其大于0.85时，灾害损失趋于稳定。²）在脆弱性曲线上拟合的值，在相同情况下，EVI比NDVI更适合指示干旱脆弱性，以估算DRP。