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Transport in Porous Media

, Volume 126, Issue 1, pp 199–222 | Cite as

Probabilistic Study of Rainfall-Triggered Instabilities in Randomly Heterogeneous Unsaturated Finite Slopes

  • Thi Minh Hue Le
  • Marcelo Sanchez
  • Domenico Gallipoli
  • Simon Wheeler
Article

Abstract

Water infiltration destabilises unsaturated soil slopes by reducing matric suction, which produces a decrease of material cohesion. If the porosity of the soil is spatially heterogeneous, a degree of uncertainty is added to the problem as water tends to follow preferential paths and produces an irregular spatial distribution of suction. This study employs the finite element method together with Monte Carlo simulations to quantify the effect of random porosity on the uncertainty of both the factor of safety and failure size of an unsaturated finite slope during and after a rainfall event. The random porosity is modelled using a univariate random field. Results show that, under partially saturated conditions, the random heterogeneity leads to a complex statistical variation of both factor of safety and failure size during the rainfall event. At any given time, the uncertainty about failure size is directly linked to the uncertainty about the position of the wetting front generated by infiltration. Interestingly, the statistical mean of the failed area is smallest when the mean of the factor of safety is lowest. In other words, the slope becomes more likely to fail, but the size of the failure mass tends to be limited. The study also investigates the sensitivity of failure uncertainty to external hydraulic parameters (i.e. initial water table depth, rainfall intensity) and internal soil parameters (i.e. permeability and water retention characteristics). In general, the sensitivity increases when the effect of these parameters on the spatial variation of suction is stronger.

Keywords

Unsaturated soils Slope Uncertainty Porosity Probabilistic 

Notes

Acknowledgements

The authors would like to acknowledge the support by the centre for research-based innovation Klima2050 - Risk reduction through climate adaptation of buildings and infrastructure to the publication of this paper.

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Thi Minh Hue Le
    • 1
  • Marcelo Sanchez
    • 2
  • Domenico Gallipoli
    • 3
  • Simon Wheeler
    • 4
  1. 1.Norwegian Geotechnical InstituteOsloNorway
  2. 2.Zachry Department of Civil EngineeringTexas A&M UniversityCollege StationUSA
  3. 3.Laboratoire SIAME, Fédération IPRAUniversité de Pau et des Pays de l’AdourAngletFrance
  4. 4.Infrastructure and Environment Research Division, School of EngineeringUniversity of GlasgowGlasgowUK

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