Preliminary debris flow risk assessment using infrastructure weighting

Debris flows are natural disasters that cause significant loss of life and property damage worldwide. In recent years, the risk of debris flows has increased due to population growth and the expansion of land use near mountainous areas driven by development pressures. Efficient debris flow risk assessment is essential to mitigate the damage caused by these disasters. Previous studies have relied on complex parameters such as fluid volume, velocity, and friction coefficients; however, this approach requires field investigations and laboratory experiments, making large-scale prediction difficult. In this study, a model was developed to predict large-scale debris flow damage and runout zones using a digital elevation model (DEM) and vector-based infrastructure data. This work focused on human casualties by incorporating the building occupancy time into the model. The model determines debris flow runout zones based on an empirical equation and risk assessment by overlaying five risk-weighting factors: distance decay weighting, spreading angle weighting, flow weighting, average slope weighting, and infrastructure weighting. To validate the model, it was applied to case studies in which human casualties were caused by a debris flow, and the results were compared with the actual damage patterns. It was found that regions classified as high-risk or greater in the risk map corresponded closely to the areas affected by the debris flows. Furthermore, the high-risk zones in the model matched the locations of buildings where human casualties occurred. This model has particular advantages as it can be quickly and easily applied using simple input data, making it a valuable tool for local governments to establish evacuation routes and proactive response strategies.