Estimation and quantitative analysis of Expected Annual Damage (EAD) caused by urban flooding: a case study of Seoul, Korea

With the rapid progression of climate change and urbanization, urban flooding has become more frequent and severe, driven by the increasing intensity and frequency of rainfall and flash floods, the expansion of impervious surfaces, and inadequate drainage systems. Accurately quantifying flood damage is essential for effective disaster management. This study estimated the Expected Annual Damage (EAD) from urban flooding in the Gangnam and Seocho districts of Seoul, South Korea. Using flood hazard maps for 30-, 50-, and 100-year return periods, flood-prone areas were identified and damage was assessed across five categories: buildings, agriculture, vehicles, human casualties, and public infrastructure. Economic losses were calculated using the exceedance probability and classified into four risk levels via a Cumulative Distribution Function (CDF). Results showed that the most severe damage would occur to vehicles, followed by buildings, public infrastructure, human beings (fatalities), and agriculture. Ilwon-dong and Seocho-dong recorded the greatest damage due to dense infrastructure and high vehicle registration. This study emphasizes the importance of including vehicle and public infrastructure damages, which have often been neglected, in flood risk assessments. The findings suggest that EAD-based approaches can guide policymakers in prioritizing protection of critical assets and improving resilience in flood-prone urban areas.