Risk assessment of rain-induced debris flow in the lower reaches of Yajiang River based on GIS and CF coupling models

Abstract: In order to reduce the adverse impact of debris flow disasters on engineering construction facilities and social security in the lower reaches of the Yajiang River, this article selected 11 risk assessment factors such as elevation, aspect, profile curvature, Relief, and rainfall to study the occurrence rule of debris flow in this area. The data of disaster factors caused by debris flow points were derived and analyzed in ArcGIS. Then, factor correlation test and factor sensitivity level were established. The coupling model of qualitative mathematical model (analytic Hierarchy Process, AHP), quantitative mathematical model (binary logistic regression [LR]), machine learning model (random forest RF), and certainty factor (CF) were, respectively, used to predict the risk of debris flow disaster in the study area. After comparison, it was found that the CF–LR model had the highest accuracy. The results show that the areas with high debris flow risk are mainly concentrated in the first half of the lower reaches of the Yajiang River and distributed along both sides of the river bank. The annual rainfall range of 600–700 mm is the critical water source saturation value of debris flow in the study area.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Risk assessment of rain-induced debris flow in the lower reaches of Yajiang River based on GIS and CF coupling models ; volume:15 ; number:1 ; year:2023 ; extent:16 ; Open Geosciences ; 15, Heft 1 (2023) (gesamt 16)

Beteiligte, Orts- und Zeitangaben

• Urheber: Yanting, Huang ; Yonggang, Guo

Weitere Informationen

• DOI: 10.1515/geo-2022-0472
• URN: urn:nbn:de:101:1-2023060314163166525614
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 2025-08-14T10:51:45+0200