Comparison of the performance of spatial landslide prediction with TRIGRS1D and SCOOPS3D models and parameter optimization: application to the Oltrepò Pavese

Physically based models based on the combination of hydrological and slope stability models are important tools in spatial and temporal prediction of landslides, since they can be used for hazard mapping as an aid for land planning. In many applications, hydrological models are combined with very simple infinite slope stability analysis, given that multi-dimensional analysis is more computationally demanding. Only a few studies have attempted to apply such algorithms to the catchment scale. Thus, there is a need for more studies on this issue, also to understand the real advantages of applying multi-dimensional slope stability analysis in comparison with the one-dimensional. 

This study aims to compare the performance of two different forecasting models, namely the infinite slope and the three-dimensional stability analysis by SCOOPS3D (Software to analyze three-dimensional slope stability throughout a digital landscape), a very efficient model proposed by USGS to be applied to the catchment scale, which has seldom been applied so far in the literature. In particular, TRIGRS (Transient Rainfall Infiltration and Grid-Based Regional Slope-stability Model) is used for hydrological analysis.  Then the resulting pressure head field is used first as input to the infinite slope stability model embedded into TRIGRS program itself and then as input to SCOOPS3D. To calibrate the terrain stability-related parameters of either piece of software, a multi-objective optimization is proposed in this work to maximize the model predictability performance, in an attempt to optimize ROC performance statistics, i.e. to maximize the true positive rate while simultaneously minimizing the false positive rate.

The approach was applied to a real case study, a catchment in the Oltrepò Pavese (northern Italy), in which the areas of triggered landslides were accurately monitored during an extreme rainfall on 27-28 April, 2009, featuring 160 mm in 48 h. Compared to other works in the scientific literature, in which only a generic point of location of landslides was known, the present work benefits from the availability of a detailed landslide inventory containing observed landslide shapes.

The results point out the significantly better performance of  SCOOPS3D, in comparison with the infinite slope stability. Though SCOOPS3D seems to overestimate landslide prone areas, the 3D method is more realistic than the 1D method as far as the slip surface definition is concerned. Therefore, the proposed methodology, lying in the use of SCOOPS 3D with optimized parameters, can be a helpful tool for providing multiple landslide hazard maps for planning.