Introduction To Urban Flood Forecasting
As the frequency of extreme rainfall events increases due to climate change, the risk of urban flooding also rises. Linear rainbands, which are narrow, elongated bands of precipitation that remain quasi-stationary over a certain area, can generate large amounts of rainfall, exceeding the drainage capacity of urban areas and leading to flooding. Sudden, intense rainfall occurring over a localized area can also rapidly raise water levels in urban streams, making it a major cause of flash floods and incidents involving people becoming stranded.
Background And Mechanisms
The Korea Institute of Civil Engineering and Building Technology (KICT) has developed an early detection technology for quasi-stationary linear rainbands and sudden localized torrential rainfall. This technology analyzes the meteorological mechanisms and characteristics of linear rainbands and sudden localized torrential rainfall to detect and predict hazardous weather conditions likely to cause water-related disasters. Using only weather radar observation data, the technology can identify and track the formation range and propagation path of rainbands, as well as the initiation and development processes and potential hazards of sudden torrential rainfall in real time.
Methodology And Application
Since November 2025, a KICT research team has participated in the Urban Flood Forecasting Task Force of the Ministry of Climate, Energy and Environment, supporting the review of key technologies required for platform development and the establishment of operational procedures. The team has applied its hazardous rainfall detection technology to the observation and monitoring functions of the Urban Flood Forecasting Platform, which is currently being piloted in areas including Gangnam and Kwanak in Seoul. The Urban Flood Forecasting Platform provides real-time detection results for rainbands and sudden downpour rainfall, enabling early identification of the likelihood of hazardous weather and providing monitoring information to support rapid assessment and decision-making regarding the potential for urban flooding.
Findings And Implications
The application of this technology to the Urban Flood Forecasting Platform is expected to contribute to faster response and securing critical response time. Dr. Yoon Seong-Sim of KICT said, "This achievement represents a notable example of putting into practice the hydrometeorological technology developed by KICT for urban water disaster response by applying it to urban flood forecasting." She added, "Once the AI-based hazardous rainfall prediction technology is fully developed, it is expected to enable flood prediction up to two hours in advance, contributing to faster response and securing critical response time." The real-time detection of hazardous rainfall will help secure additional time for proactive response, reducing the risk of urban flooding and related incidents.
Future Outlook And Development
The development of this technology is an important step towards improving urban flood forecasting and reducing the risk of water-related disasters. The application of AI-based hazardous rainfall prediction technology is expected to further enhance the accuracy and speed of flood prediction, enabling more effective response and mitigation measures. As the frequency and severity of extreme rainfall events continue to increase, the importance of advanced technologies like this will only continue to grow, highlighting the need for ongoing research and development in this field.
Sources
This is an original synthesis by Qivorane based on reporting from the outlets below.
