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Conference Paper
Predictive Methodology for Cascading Disasters/Events Induced by Extreme Rainfall in Urban Areas
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- Authors
- Seunghee Oh, Yoon-Seop Chang
- Issue Date
- 2026-05
- Citation
- European Geosciences Union General Assembly (EGU) 2026, pp.1-1
- Publisher
- Copernicus GmbH
- Language
- English
- Type
- Conference Paper
- Abstract
- Climate change has increased the intensity and frequency of hazard events, resulting in disaster risks that exceed historical experience. In highly urbanized countries such as South Korea, heavy and extreme rainfall has become a major climate-related hazard, leading to concentrated human and economic losses. While extreme rainfall can be partially anticipated through meteorological radar observations, official forecasts, and pattern-based prediction models, such hazard-focused approaches are insufficient to fully assess disaster risk in urban areas. This is because actual impacts are strongly influenced by exposure, vulnerability, and cascading effects, which may evolve into complex disasters. In line with the IPCC and UNDRR disaster risk framework, this study emphasizes the need to anticipate secondary hazards and cascading risk events that may develop into complex disasters under extreme rainfall conditions. To address this challenge, a scenario generation method for extreme rainfall–induced complex disasters is proposed. The method integrates three key components: (1) regional exposure and vulnerability characteristics, including population distribution, industrial activities, transportation networks, and critical infrastructure; (2) secondary hazard and impact information derived from historical disaster records; and (3) interrelationships and correlations among different hazard and disaster types. Using a weighted analytical framework, the proposed approach generates representative scenarios with high likelihood as well as extreme scenarios with lower likelihood but potentially high impacts. These scenarios support a risk-informed understanding of possible disaster pathways and provide actionable prior information for preparedness planning, emergency response, and scenario-based training. The results contribute to strengthening disaster risk reduction and enhancing urban resilience against climate-related extreme rainfall–induced complex disasters.
- KSP Keywords
- Cascading effect, Climate Change, Critical Infrastructure, Disaster risk reduction, Economic losses, Extreme scenarios, Historical experience, Key Components, Pattern-based, Population distribution, Radar observations