# Simulation of Debris-Flow Runout Near a Construction Site in Korea
## 1 Introduction  
Landslides are a major geological hazard, which can result in the loss of human life and economic damage, in many areas on Earth. According to the Centre for Research on Epidemiology of Disasters, landslides are responsible for 17% of the world's natural hazard fatalities [1]. 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. Physically 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]. In probabilistic analysis methods, several parameters are considered as random variables and the statistical parameters and probability density functions of uncertain variables are estimated [8; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21]. Using soil, rock, and slope maps, such analysis can identify areas of high landslide potential within a regional area. Several statistical methods can be used in probabilistic analyses to evaluate landslide susceptibility. Among these, logistic regression analysis is commonly used because its results are considered the most reliable [22; 23; 24; 25; 26]. Logistic regression is a useful method, and applicable to landslide occurrence, when the dependent variable is categorical,and the independent variables are categorical and/or numerical. According to [27], logistic regression has been chosen for many studies because: (i) it is one of the most common statistical methods used to model landslide susceptibility, (ii) logistic regression has the lowest rate of error, increasing confidence in the results of any comparison, (iii) logistic regression generates a statistical significance value for each covariate in the model, and (iv) logistic regression estimates probabilities of landslide susceptibility and hazard.  
For landslide damage assessment, landslide runout has been modeled based on topography, the properties of the slide materials, and soil water content. Fast landslides, such as debris flows, tend to accelerate below the initial failure, and when their displacements are of high volume, they can cause critical damage, and many casualties, in the area hit by the landslide. This makes the prediction of landslide runout necessary to encourage preparedness and reduce damage. Many studies have sought to model landslide runout by considering the properties, volumes, and mobilities of the moving materials [28; 29; 30; 31; 32; 33; 34; 35].  
Since 2000, in the Korean Peninsula, the number of landslide events on natural terrain has increased continuously under the influence of increasing rainfall amounts and durations as a consequence of climate change. Considering the seriousness of landslide hazards in Korea, this study analyzed landslide susceptibility and simulated debris flows runout distances near a construction site in Chooncheon, Korea. Many landslides occurred in Chooncheon in July 2011 and July 2013 resulting in huge damage to local people and their properties. Community infrastructure was planned at the construction site at the bottom of a mountain necessitating a comprehensive evaluation of the safety of the facility. Therefore, to estimate the likelihood of damage to the site, this study used a landslide prediction map of the area, which had been drawn in 2008 with a logistic regression model suggested by [14], to determine landslide susceptibility. The authors then simulated debris-flow runout distances in the major watersheds around the construction site. There have been few prior runout distance modeling studies in Korea and prediction of runout distances is rare. An exception is the Debris-2D model [36; 37] for simulation of runout distances under Korean geologic and topographic conditions. Debris-2D was therefore used for this study.