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Lookup NU author(s): Dr Xilin Xia, Professor Qiuhua Liang
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Flow-like landslides are one of the most catastrophic types of natural hazards due to their high velocity and long travel distance. They travel like fluid after initiation and mainly fall into the ‘flow’ movement type in the updated Varnes classification (Hungr et al., 2014). In recent years, depth-averaged models have been widely reported to predict the velocity and run-out distance of flow-like landslides. However, most of the existing depth-averaged models present different shortcomings for application to real-world simulations. This paper presents a novel depth-averaged model featured with a set of new governing equations derived in a mathematically rigorous way based on the shallow flow assumption and Mohr-Coulomb rheology. Particularly, the new mathematical formulation takes into account the effects of vertical acceleration and curvature effects caused by complex terrain topographies. The model is derived on a global Cartesian coordinate system so that it is easy to apply in real-world applications. A Godunov-type finite volume method is implemented to numerically solve these new governing equations, together with a novel scheme proposed to discretise the friction source terms. The hydrostatic reconstruction approach is implemented and improved in the context of the new governing equations, providing well-balanced and non-negative numerical solutions for mass flows over complex domain topographies. The model is validated against several test cases, including a field-scale flow-like landslide. Satisfactory results are obtained, demonstrating the model's improved simulation capability and potential for wider applications.
Author(s): Xia X, Liang Q
Publication type: Article
Publication status: Published
Journal: Engineering Geology
Year: 2018
Volume: 234
Pages: 174–191
Online publication date: 31/01/2018
Acceptance date: 14/01/2018
Date deposited: 08/02/2018
ISSN (print): 0013-7952
ISSN (electronic): 1872-6917
Publisher: Elsevier
URL: https://doi.org/10.1016/j.enggeo.2018.01.011
DOI: 10.1016/j.enggeo.2018.01.011
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