A similarity-based quantitative model for assessing regional debris-flow hazard

Debris flows belong to sudden disasters which are difficult to forecast. Thus, a detailed and coherent hazard assessment seems a necessary step to prevent or relieve such disasters and mitigate the risk effectively. Previous researchers have proposed several methods, such as regression analysis, fuzzy mathematics, and artificial neural networks for debris-flow hazard assessment. However, these methods need further improvements to eliminate the high relativity existing in their results. The current study reported a similarity-based debris-flow hazard assessment model to determine hazard levels of debris flow in regions, with steps like determining hazard-level-type regions, selecting environmental factors and calculating the similarities between the assessment-pending regions and assessed hazard-level-type ones. This methodology was then employed to assess the regional debris hazard of Yunnan Province in China as a case study and was verified via comparison with field surveys. As the results indicate, the proposed similarity-based debris-flow risk assessment model is simple and efficient and can improve the comparability and reliability of the assessment to some degree.