A Review of Current Techniques for Debris Flow Susceptibility Assessment

Abstract

In the mountain region, debris flows are among the most recognized geological natural hazards, due to their unpredictability, rapid movement, and extensive runout distribution, which have been documented for several centuries. For reliable and efficient mitigation measures, debris flow susceptibility assessment (DFSA) is an essential approach. Over the past few decades, numerous methods have been developed to evaluate debris flow susceptibility. In this article, the authors study and discuss current techniques for DFSA in detail. These techniques are grouped into the following approaches: Qualitative, Semi-quantitative, and Quantitative. 30 research articles published between 2016 and 2025 were analyzed. Across the studies, 25 susceptibility assessment techniques were identified; among these, random forest (RF), logistic regression (LR), Support vector machine (SVM), and extreme gradient boosting (XGBoost) are most frequently employed. Overall, this article provides a comprehensive discussion of debris flow susceptibility assessment and serves as a valuable reference for scientists and researchers.