To proactively prevent losses from flood disasters and subsequent potential human conflicts, it is critical to measure the social vulnerability of a country or a region to flood. In this article, we first propose a list of potential indicators for measuring this social vulnerability. These indicators’ significances are then tested based on their correlation coefficients with a vulnerability index obtained using nonparametric Data Envelopment Analysis. In the final measurement system, there are nine indicators: the proportion of the primary industry, infrastructure development level, income gap between urban and rural residents, the proportion of population over 60 years old, the proportion of children under 14 years old, the number of people receiving minimum income assistance, and the number of disasters per year. We then conduct principal component analysis to evaluate the social vulnerability level. Our results show that the social vulnerability level is mostly impacted by the economic principal component and the demographic and social security principal component. Moreover, our results also confirm that the social vulnerability level to flood in China declined overall from 2003 to 2015.
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