Browse by author
Lookup NU author(s): Dr David Milledge
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
The size of a shallow landslide is a fundamental control on both its hazard and geomorphic importance. Existing models are either unable to predict landslide size or are computationally intensive such that they cannot practically be applied across landscapes. We derive a model appropriate for natural slopes that is capable of predicting shallow landslide size but simple enough to be applied over entire watersheds. It accounts for lateral resistance by representing the forces acting on each margin of potential landslides using earth pressure theory and by representing root reinforcement as an exponential function of soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are well constrained by field data. The model predicts failure for the observed scar geometry and finds that larger or smaller conformal shapes are more stable. Numerical experiments demonstrate that friction on the boundaries of a potential landslide increases considerably the magnitude of lateral reinforcement, relative to that due to root cohesion alone. We find that there is a critical depth in both cohesive and cohesionless soils, resulting in a minimum size for failure, which is consistent with observed size‐frequency distributions. Furthermore, the differential resistance on the boundaries of a potential landslide is responsible for a critical landslide shape which is longer than it is wide, consistent with observed aspect ratios. Finally, our results show that minimum size increases as approximately the square of failure surface depth, consistent with observed landslide depth‐area data.
Author(s): Milledge DG, Bellugi D, McKean JA, Densmore AL, Dietrich WE
Publication type: Article
Publication status: Published
Journal: Journal of Geophysical Research: Earth Surface
Print publication date: 01/11/2014
Online publication date: 21/10/2014
Acceptance date: 15/10/2014
Date deposited: 26/07/2018
ISSN (print): 2169-9003
ISSN (electronic): 2169-9011
Publisher: Wiley-Blackwell Publishing, Inc.
Altmetrics provided by Altmetric