- Seoul National University of Science and Technology, Civil Engineering Systems, Water Resources Systems, Seoul, Korea, Republic of (ssong000826@gmail.com)
The frequency of unprecedented localized torrential rainfalls, such as the 2024 heavy rainfall event in South Korea, has been increasing due to climate change. Simultaneously, urbanization has intensified the development of underground spaces and excavation sites due to population concentration. This study assesses the risks associated with evacuation routes in various types of underground spaces during extreme rainfall events and develops a real-time flood prediction and early warning system that incorporates evacuation lead time analysis.
A testbed was established in a watershed that experiences chronic flooding caused by the combined effects of seawater intrusion, external runoff, and internal drainage issues. Using Arc-GIS, a detailed topographic model was constructed for the region. To analyze dynamic flood risks under real-time rainfall conditions, novel rainfall scenarios were created by combining observed rainfall data from rain gauges with predicted rainfall data from radar systems. Observed rainfall from rain gauges within the watershed, measured up to one hour prior, was distributed according to Huff’s 4th quartile pattern, while predicted rainfall for the subsequent 30 minutes was distributed using Huff’s 1st quartile pattern. These patterns were combined to simulate the worst-case scenario, representing the most challenging evacuation conditions.
These datasets provided the foundational framework for conducting two-dimensional flood simulations using XP-SWMM. The risks along evacuation routes were quantified by calculating the product of flood depth and flow velocity(hv). Furthermore, a flood risk nomograph was developed, and alert levels were defined based on the timing of risk escalation.
The real-time flood prediction and early warning system proposed in this study has the potential to be applied to flood-prone disaster zones across the country. By evaluating evacuation route risks under various rainfall scenarios, this system enables the timely transmission of evacuation alerts and warnings to minimize disaster impacts.
How to cite: Lee, S. I., Kim, J., Kim, K., Kang, J., and Jun, H.: Development of a Real-Time Flood Prediction and Early Warning System for Underground Spaces, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4004, https://doi.org/10.5194/egusphere-egu25-4004, 2025.
