Risk assessment of debris flow disaster based on the cloud model-Probability fusion method.

Content Provider	Europe PMC
Author	Li, Li Ni, Bo Qiang, Yue Zhang, Shixin Zhao, Dongsheng Zhou, Ling
Editor	Muhammad, Sher
Copyright Year	2023
Abstract	This paper proposes a new debris flow risk assessment method based on the Monte Carlo Simulation and an Improved Cloud Model. The new method tests the consistency of coupling weights according to the characteristics of the Cloud Model firstly, so as to determine the weight boundary of each evaluation index. Considering the uncertain characteristics of weights, the Monte Carlo Simulation is used to converge the weights in a minimal fuzzy interval, then the final weight value of each evaluation index is obtained. Finally, a hierarchical comprehensive cloud is established by the Improving Cloud Model, which is used to input the comprehensive expectation composed of weights to obtain the risk level of debris flow. Through statistical analysis, this paper selects Debris flow scale (X1), Basin area (X2), Drainage density (X3), Basin relative relief (X4), Main channel length (X5), Maximum rainfall (X6) as evaluation indexes. A total of 20 debris flow gullies were selected as study cases (8 debris flow gullies as model test, 12 debris flow gullies in reservoir area as example study). The comparison of the final evaluation results with those of other methods shows that the method proposed in this paper is a more reliable evaluation method for debris flow prevention and control.
Page Count	18
Journal	PLOS ONE
Volume Number	18
DOI	10.1371/journal.pone.0281039
PubMed Central reference number	PMC9894451
Issue Number	2
PubMed reference number	36730340
e-ISSN	19326203
Language	English
Publisher	Public Library of Science
Publisher Date	2023-02-02
Publisher Place	San Francisco, CA USA
Access Restriction	Open
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary