Framework of Emergency Response System for Potential Large-Scale Landslide in Taiwan

• Main Authors: Yuan-Jung Tsai, Fang-Tsz Syu, Chjeng-Lun Shieh, Chi-Rong Chung, Shih-Shu Lin, Hsiao-Yuan Yin
• Format: Article
• Language: English
• Published: MDPI AG 2021-03-01
• Series: Water
• Subjects: large-scale landslide; hazard mapping; pre-warning; emergency response
• Online Access: https://www.mdpi.com/2073-4441/13/5/712

In order to lower the risks of large-scale landslides and improve community resilience in Taiwan, a long-term project has been promoted by the Soil and Water Conservation Bureau since 2017. In this study, methods to build an emergency response framework including hazard mapping and early warning system establishment were introduced. For hazard mapping, large-scale landslides were categorized into a landslide, debris flow, or landslide dam type based on the movement of unstable materials and topography. Each disaster type has different hazard zone delineation methods to identify the affected areas. After establishing the possible effected areas, early warning mechanisms, including warning value using rainfall as the indicator and evacuation procedures, should be created for emergency response. To set the warning value, analysis of the occurrence thresholds of previous existing large-scale landslides was conducted to determine the critical rainfall and further utilized to set the warning value considering the evacuation time for the locals. Finally, for integration with the current debris flow emergency response system, potential large-scale landslide areas were further divided into two types based on their spatial relationship with debris flows. For those overlapping with existing debris flow protected targets, the current emergency response system was upgraded considering the impact of large-scale landslides, while the others were suggested for use in building a new emergency response procedure. This integrated framework could provide a feasible risk avoidance method for local government and residents.