Different Methods to Produce Distributed Soil Thickness Maps and Their Impact on the Reliability of Shallow Landslide Modeling at Catchment Scale

In this paper we made a comparison between various methods to enter soil thickness as a spatial variable in a deterministic basin scale slope stability simulator. We used a slope stability model that couples a simplified solution of Richards infiltration equation and an infinite slope model with soil suction effect. Soil thickness was entered in the stability modelling using spatially variable maps obtained with four state-of-art methods: linear correlation with elevation; linear correlation with slope gradient; exponential correlation with slope gradient; a more complex geomorphologically indexed model (GIST model). Soil thickness maps and the derivate Factor of Safety (FS) maps were validated. Results confirmed that FS is very sensitive to soil thickness and showed that the same slope stability model can be highly sensitive or highly specific depending on the input soil thickness data. The uncertainty in the FS calculation can be reduced by applying more precise soil thickness input data: mean error of soil thickness maps is closely related to the sensitivity or specificity of the FS computation, while the overall performance of the stability simulation depends on mean absolute error and skewness of the frequency distribution of the errors of soil thickness maps. Despite the fact that slope-based methods are the most used in literature to derive soil thickness, in our application they returned poor results. Conversely, the use of the GIST model improved the performance of the stability model.