Incorporating the effects of complex soil layering and thickness local variability into distributed landslide susceptibility assessments
Incorporating the influence of soil layering and local variability into the parameterizations of physics-based numerical models for distributed landslide susceptibility assessments remains a challenge. Typical applications employ substantial simplifications including homogeneous soil units and soil-hydraulic properties assigned based only on average textural classifications; the potential impact of these assumptions is usually disregarded. We present a multi-scale approach for parameterizing the distributed Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model that accounts for site-specific spatial variations in both soil thickness and complex layering properties by defining homogeneous soil properties that vary spatially for each model grid cell. These effective properties allow TRIGRS to accurately simulate the timing and distribution of slope failures without any modification of the model structure. We implemented this approach for the carbonate ridge of Sarno Mountains (southern Italy) whose slopes are mantled by complex layered soils of pyroclastic origin. The urbanized foot slopes enveloping these mountains are among the most landslide-prone areas of Italy and have been subjected to repeated occurrences of damaging and deadly rainfall-induced flow-type shallow landslides. At this scope, a primary local-scale application of TRIGRS was calibrated on physics-based rainfall thresholds, previously determined by a coupled VS2D (version 1.3) hydrological modeling and slope stability analysis. Subsequently, by taking into account the spatial distribution of soil thickness and vertical heterogeneity of soil hydrological and mechanical properties, a distributed assessment of landslide hazard was carried out by means of TRIGRS. The combination of these approaches led to the spatial assessment of landslide hazard under different hypothetical rainfall intensities and antecedent hydrological conditions. This approach to parameterizing TRIGRS can be adapted to other spatially variable soil layering and thickness to improve hazard assessments.