Debris Flow Classification and Risk Assessment Based on Combination Weighting Method and Cluster Analysis: A Case Study of Debris Flow Clusters in Longmenshan Town, Pengzhou, China

• Published in: Applied sciences Vol. 13; no. 13; p. 7551
• Main Authors: Li, Yuanzheng, Shen, Junhui, Huang, Meng, Peng, Zhanghai
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2023
• Subjects: Algorithms; Artificial intelligence; Case studies; Classification; classification of debris flows; Cluster analysis; combination weighting method; Earthquakes; Flow velocity; Geological surveys; Geology; Longmenshan Town; Methods; National scenic areas; Onsite; optimization; Rain; Remote sensing; Risk assessment; Simulation; Urban areas; Vegetation; China
• DOI: 10.3390/app13137551
• ISSN: 2076-3417

Debris flows can damage infrastructure and threaten human life and property safety, especially in tourist attractions. Therefore, it is crucial to classify and evaluate the risk of debris flows. This article takes 14 debris flows in Longmenshan Town, Pengzhou, Sichuan, China, as the research object. Based on on-site geological surveys, combined with drone images and multiple remote sensing images, the essential characteristics of each debris flow are comprehensively determined. A total of nine factors are used as the primary indicators affecting the risk of debris flow: drainage density, roundness, the average gradient of the main channel, maximum elevation difference, bending coefficient of the main channel, the loose-material supply length ratio, vegetation area ratio, population density, and loose-material volume of unit area. The subjective weights of each indicator are obtained using the Analytic Hierarchy Process, while the objective weights are obtained using the CRITIC method. Based on this, the distance function is introduced to couple the subjective and objective weights, determine each indicator’s combined weights, and obtain the integrated evaluation score values of different debris flow hazards. Considering the integrated evaluation score of debris flow, cluster analysis was used to classify 14 debris flows and cluster effectiveness indicators were introduced to determine the effectiveness of debris flow classification. A quantitative standard for the risk of debris flow within the study area was proposed, and finally, a risk assessment of debris flow in the study area was made. Comparing the results of this paper with the gray correlation method, the coupled synergistic method, and the geological field survey results, proves that the proposed method is feasible and provides a reasonable scientific basis for the study of the hazard assessment of regional debris flow clusters and other related issues within the scope of the Jianjiang River basin and other areas.