Modelling for the automatic assessment of rainfall triggered landslide susceptibility due to changes in groundwater level and soil water content.

Risk assessment of rain-triggered landslides over large areas is quite challenging due to the complexity of the phenomenon. In fact, rainfall represents one of the most important triggering factors for landslides performing an erosive action at ground level, and, through deep infiltration, increasing the soil saturation degree and feeding the groundwater table leading to fluctuations that can affect the slope stability. These phenomena represent an open challenge for technicians and authorities involved in landslide risk management and mitigation. For this reason, it is necessary to develop appropriate models for the landslides susceptibility assessment that are operationally compatible with good resolution and computational speed. Standard methods of 3D slope stability analysis are generally applied over limited areas or at low resolution. In this dissertation, two automatic procedures are proposed for estimating landslide susceptibility induced by changes in (i) groundwater levels and (ii) soil saturation conditions. A physically based Integrated Hydrological and Geotechnical (IHG) model was implemented in GIS environment to effectively analyse areas of a few square kilometres, typically at a scale of 1:5.000. Referring to each volume element in which the whole mass under study is discretized, a simplified hydrological soil-water balance and geotechnical modelling are applied in order to assess the debris and earth slide susceptibility in occasion of measured or forecasted rainfalls. The IHG procedure allows 3D modelling of landslide areas, both morphologically and with regard to geotechnical/hydrological parameters thanks to the spatialisation of input data from in situ measurements, and renders easy-to-understand results. Critical issues inherent the discretization of quite large areas, referred to soil characterization, interpolation/extrapolation of in situ measurements, spatial resolution and computational effort, are here discussed. Considering rain-triggered shallow landslides, the stability can be markedly influenced by the propagation of the saturation front inside the unsaturated zone. Soil shear strength varies in the vadose zone depending on the type of soil and the variations of soil moisture. Monitoring of the unsaturated zone can be done by measuring volumetric water content using low-cost instrumentation (i.e. capacitive sensors) that are easy to manage and provide data in near-real time. For a proper soil moisture assessment a laboratory soil-specific calibration of the sensors is recommended. Knowing the soil water content, the suction parameter can be estimated by a Water Retention Curve (WRC), and consequently the soil shear strength in unsaturated conditions is evaluated. The automatic procedure developed in GIS environment, named assessment of Soil Apparent Cohesion (SAC), here described, allows the estimate of the soil shear strength starting from soil moisture monitoring data (from sensor networks or satellite-derived map). SAC results can be integrated into existing models for landslide susceptibility assessment and also for the emergency management. Some significant results concerning the automatic IHG and SAC procedures, implemented in Python, applied to landslides within the Alcotra AD-VITAM project are here presented.