Improving urban flood forecasting with real-time hazardous rainfall detection

The Korea Institute of Civil Engineering and Building Technology (KICT) announced that it will apply its early detection technology for quasi-stationary linear rainbands and sudden localized torrential rainfall to the Urban Flood Forecasting Platform operated by the Han River Flood Control Office in Korea for urban flood forecasting.

As extreme rainfall events become more frequent due to climate change, the risk of urban flooding is also increasing. In particular, linear rainbands—narrow, elongated bands of precipitation that remain quasi-stationary over a certain area and produce large amounts of rainfall—can generate rainfall exceeding the drainage capacity of urban areas, 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, rapid currents and incidents involving people becoming stranded.

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 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.

The Urban Flood Forecasting Platform provides real-time detection results for rainbands and sudden downpour rainfall. This enables early identification of the likelihood of hazardous weather and provides monitoring information to support rapid assessment and decision-making regarding the potential for urban flooding, helping secure additional time for proactive response.

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.”

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Robert Egan

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