A socio-economic vulnerability assessment framework against natural disasters: A case study in Seoul, South Korea

Recent publications on vulnerability assessment of weather-related disasters exhibit three main drawbacks: (1) minimal explanation of high contributing features; (2) limited validation; and (3) partial presentation of validation results. Our research addresses these gaps by thoroughly examining the most influential factors on the Socio-Economic Vulnerability Index (SEVI). We internally validated SEVI using Monte Carlo simulation, providing an in-depth evaluation of uncertainties in both values and rankings, along with sensitivity analysis of features. Seoul was selected in this study due to its status as South Korea's largest metropolitan city and its vulnerability to natural disasters. The findings reveal: (1) demographic structure features mainly drive the distribution of highly vulnerable sub-districts around the Han River; (2) among 38 highly vulnerable sub-districts, 15 exhibit low bias in SEVI values, while 10 remain unchanged in rankings, supporting reliable flood risk mitigation strategies; (3) the single-mom family feature causes the highest variability in SEVI results, exceeding 5 %. These findings emphasize the need for disaster risk management strategies to be deeply informed by socio-economic and demographic data. By integrating these insights into planning, policymakers can develop more effective strategies, addressing both immediate disaster impacts and the underlying vulnerabilities that make certain populations more susceptible to harm.