Rainfall-induced flow-like landslides in unsaturated pyroclastic soils represent a significant geohazard in Southern Italy. These phenomena are closely linked to reductions in matric suction and subsequent loss of shear strength during intense or prolonged rainfall events. This study proposes an integrated framework for producing continuously updatable slope-stability maps by coupling real-time field monitoring with GIS-based spatial modelling. The approach was applied to a test site located on Faito Mt. in the Lattari Mountains (Campania, Southern Italy), an area historically affected by flow-like landslides. The field site was instrumented with a comprehensive monitoring network recording suction and volumetric water content (VWC) at multiple depths over a two-year period. These data were used to assess cell-based distributed slope stability conditions in GIS, considering each cell as an infinite slope. The results were successively compared with those obtained using the Limit Equilibrium Method (LEM) applied to cross-sections representative of the actual slope geometry. In this way, it was possible to evaluate the GIS-based model outputs and to understand the influence of stratigraphy and the local factors on slope stability. This comparison highlighted that simplified model, although efficient for large-scale screening, may misrepresent slope stability condition when the local factors and the irregularities in stratigraphy and in buried morphology are ignored. This study supports the development of real-time updatable susceptibility assessments for flow like-landslide triggering by integrating local hydraulic monitoring into spatial stability modelling. In particular, the proposed approach offers promising potential for implementation in operational early warning systems for pyroclastic soils prone to flow-like landslides. • Field suction and moisture data integrated into GIS-based stability models. • Seasonal suction changes strongly modulate slopes' factor of safety. • Hydraulic state determines the layer most prone to triggering. • Framework supports near-real-time updates for landslide early warning use.
Luise et al. (Fri,) studied this question.