Securing the 'Landslide Golden Time' Using Rainfall Information

[Asia Economy Reporter Hwang Junho] A system that predicts and notifies the location, timing, and extent of damage from landslides using rainfall information forecasted at least one day in advance has been developed. It is expected to contribute to minimizing casualties caused by landslides.

The Korea Institute of Geoscience and Mineral Resources (KIGAM) announced on the 24th that it has developed an early warning system for landslides based on landslide monitoring technology optimized for Korea's geological and ground characteristics, physics-based landslide prediction methods, and prior meteorological information.

This system is notable for securing the golden time to reduce landslide damage. It integrates landslide prediction technology that identifies areas where landslides may occur using various rainfall information predicted one day in advance and mathematical dynamic analysis methods, enabling relatively accurate identification of potential landslide locations and expected occurrence times. The system utilizes relatively accurate prior rainfall data from Korea Meteorological Administration’s local forecasts, Japan Meteorological Agency’s weather radar data, and KIGAM’s own rainfall monitoring data.

KIGAM is currently piloting and operating this system over a 20.6㎢ area around Jirisan National Park (near Cheonwangbong Peak). The research team reported that landslide occurrence reproduction calculations based on landslide history and rainfall data in the study area confirmed high accuracy.

Song Youngseok, Director of the Geological Environment Disaster Research Center, stated, "The early warning system for landslides linked with prior rainfall information developed by KIGAM is effectively operated in disaster prevention advanced countries such as Italy and Japan to reduce landslide damage. We will do our best to develop world-class early warning technology optimized for Korea’s terrain and ground conditions."

This content was produced with the assistance of AI translation services.