Evaluating the spatial uncertainty in the modelling of landlides: The Boolean Stochastic Generation (BoSG) method

In common practice, when designing a geotechnical model of a landslide, some stratigraphic details are usually discarded in order to simplify the problem. This approach is supported by the hypothesis that the significance of the results of the model would not be affected, besides additional uncertainty associat-ed with the thickness and lateral extent of these minor strata is avoided. In this work a new method called Boolean Stochastic Generation (BoSG) which relies on a Monte Carlo generation of numerous soil layers dis-tributions following a Boolean logic (the material is either matrix or layer) is associated with the Point Esti-mate Method. This association allows to determine the influence of thevariation of the soilparameters of the matrix materialin theBoSG runs. The Mortisa landslide was selected ascase study as it shows a soil compo-sition particularly suitable for BoSG: gravel lenses interdigitated in a silty-clay matrix. Results show that the bigger is the difference between matrix and layer properties, the greater is the influence of more resistant lay-ers as they are intercepted by the plastic deformation.Moreover, studying the distribution of the uncertainty along the slope may help to indicate where to perform a secondary investigation campaign.