Numerical analysis of debris flow erosion in the mountainous areas affected by the 2008 Wenchuan earthquake using a depth-averaged two-phase model

Hualin Cheng, Martin Mergili and Yu Huang ()
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Hualin Cheng: Tongji University
Martin Mergili: University of Graz
Yu Huang: Tongji University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 116, issue 1, No 9, 193-212

Abstract: Abstract Channel bed erosion accompanying debris flows can significantly magnify the flowing mass and increase the associated risk. However, the mechanics of this geological phenomenon is extremely complex, which greatly increases the difficulty of predicting the dynamical behavior and bulking process of large-scale debris flows. This study employs the depth-averaged two-phase r.avaflow model to numerically analyze the flow propagation and sediment erosion processes. Two modified empirical erosion laws are further embedded in the r.avaflow framework to comparatively compute the channel erosion of a typical catastrophic debris flow occurring in Wenchuan earthquake-affected mountainous areas. The results show that both of the two erosion models can effectively reproduce the movement and channel erosion of the debris flows under investigation. In addition, the most serious sediment erosion has been found to occur along the two sides of the channels. Additionally, r.avaflow model with its simple CE-controlled erosion law relating the erosion coefficient to the slope topography is further applied to predict the dynamical behavior and bulking process of the Hongchun gully debris flow under 50- and 100-year recurrence intervals. The discharge and hazard intensity are shown to greatly increase under the effect of the typically ignored sediment erosion. This study provides more scientific basis for risk assessment and hazard mitigation for large-scale debris flows in mountainous areas.

Keywords: Debris flow; Erosion; Two-phase numerical model; Mountainous areas; Wenchuan earthquake (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-022-05669-1

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