Simulation of Debris-Flow Runout Near a Construction Site in Korea

Byung-Gon Chae,Ying-Hsin Wu,Junghae Choi,Ko-Fei Liu,Hyuck-Jin Park

doi:10.3390/app10176079

Abstract

This study analyzed landslide susceptibility and numerically simulated the runout distance of debris flows near a construction site in Korea. Landslide susceptibility was based on a landslide prediction map of the study area. In the prediction map, 3.5% of the area had a 70–90% landslide probability, while 0.79% had over 90% probability. Based on the landslide susceptibility analysis, debris flows in four watersheds were simulated to assess possible damage to the construction site. According to the simulations, debris flow in Watershed C approaches to within 9.6 m of the site. Therefore, the construction site could be impacted by debris flow in Watershed C. Although the simulated flows in Watersheds A and D do not directly influence the construction site, they could damage the nearby road and other facilities. The simulations also show that debris runout distance is strongly influenced by the volume of debris in the on-slope source area and by the slope angles along the debris-flow path.

Highlights

Landslides are a major geological hazard, which can result in the loss of human life and economic damage, in many areas on Earth
Since the major objective of this study was to assess the safety of the construction site, site, relative to debris flows from
The location of the construction site appears to be vulnerable to debris flows from two valleys, both with areas of landslide probability over 70%

Summary

Introduction

Landslides are a major geological hazard, which can result in the loss of human life and economic damage, in many areas on Earth. To reduce damage from landslides, many scientific studies have sought to predict landslide occurrence and evaluate runout distances. Landslide prediction research has used both physically based landslide susceptibility methods and probabilistic analysis methods. Based landslide susceptibility assessment methods usually base a landslide initiation model on the physical properties of the soils and rocks on slopes and so predict slope instability [2,3,4,5,6,7,8,9,10]. Several statistical methods can be used in probabilistic analyses to evaluate landslide susceptibility. Logistic regression analysis is commonly used because its results are considered the most reliable [22,23,24,25,26].

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Discussion

Conclusion