, Volume 16, Issue 11, pp 2277–2286 | Cite as

Modelling of an accidentally triggered shallow landslide in Northern Italy

  • Alex SanzeniEmail author
  • Marco Peli
  • Stefano Barontini
  • Francesco Colleselli
Technical Note


The paper presents a case study of a landslide event, accidentally triggered by an unexpected and extraordinary infiltration in an otherwise stable slope. The work aims at modelling the slope failure mechanism with a simplified two-dimensional framework based on the formation of a perched water table. The landslide occurred in Val Venosta/Vinschgau Valley, in Northern Italy, in April 2010 and produced catastrophic consequences. It took place on a hillside with average slope angle 36° and affected an area of about 200 m2; the slip surface was located approximately 1.0 m below the slope profile, in the uppermost layers of a predominantly coarse, well-graded soil. A series of numerical simulations were performed to back-analyse the event, using a commercial computer program. The artificial water infiltration and water content evolution were modelled with a two-dimensional finite element model (FE) of the unsaturated/saturated domain with appropriate infiltration boundary conditions. The slope stability analyses were conducted with a classic limit equilibrium method (LE) and were performed at different time instants during the infiltration process. The soil-water retention curves and conductivity functions were defined according to the van Genuchten-Mualem model. The combined FE and LE simulations showed the gradual formation of a perched water table, whose associated localized pore pressure distribution resulted in the loss of the suction stabilizing effect and thus in the reduction of the safety factor. Although supported by basic soil mechanical and hydraulic characterization, the numerical simulations allowed to perform a back-analysis which effectively captured the timing of the event and the location and depth of the slip surface along the slope.


Landslide Infiltration Modelling Back-Analysis 


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© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.DICATAMUniversità degli Studi di BresciaBresciaItaly

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