Abstract
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.
Highlights
Periodic flood disasters have caused enormous losses in China
Integrated flood risk management emphasizes that flood disasters have important social dimensions and human society is “vulnerable” [2]
Li et al [7] investigated the socio-economic factors of Jingzhou City from 2001 to 2012 to establish an index system of social vulnerability to flood disaster from the perspectives of social sensitivity and social coping ability, and assessed the social vulnerability to floods based on entropy method
Summary
Periodic flood disasters have caused enormous losses in China. For example, the number of deaths caused by floods since 1950 in China totals around 280,000. Assessing social vulnerability to flood is important because it can reveal the major contributing factors in flood disaster recovery [5]. We make a major contribution by establishing a quantification method for the social vulnerability to flood disasters in China where we incorporate more comprehensive perspectives such as the technological perspective. We conduct principal component analysis and confirm that social vulnerability to flood is impacted the most by economic, demographic, and social security factors. We obtain the social vulnerability level to flood disasters in China from 2003 to 2015 This is our third contribution as little research has been done on the social vulnerability to flood disasters using the combined methodologies of DEA, correlation coefficient analysis, and principal component analysis.
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