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Performing a reliable stability analysis of a landslide slope requires a good understanding of the internal geometries and an accurate characterisation of the geotechnical parameters of the identified strata. Geotechnical models are commonly based on geomorphological data combined with direct and intrusive geotechnical investigations. However, the existence of numerous empirical correlations between seismic parameters (e.g., S-wave velocity) and geotechnical parameters in the literature has made it possible to investigate areas that are difficult to reach with direct instrumentation. These correlations are often overlooked even though they enable a reduction in investigation costs and time. By means of geophysical tests, it is in fact possible to estimate the N-SPT value and derive the friction angle from results obtained from environmental seismic noise measurements. Despite the empirical character and a certain level of uncertainty derived from the estimation of geotechnical parameters, these are particularly useful in the preliminary stages of an emergency, when straight data are not available and on all those soils where other direct in situ tests are not reliable. These correlations were successfully applied to the Theilly landslide (Western Alps, Italy), where the geotechnical model was obtained by integrating the results of a multi-parameter geophysical survey (H/V seismic noise and ground-penetrating radar) with stratigraphic and geomorphological observations, digital terrain model and field survey data. The analysis of the triggering conditions of the landslide was conducted by means of hydrological–geotechnical modelling, evaluating the behaviour of the slope under different rainfall scenarios and considering (or not) the stabilisation interventions present on the slope. The results of the filtration analyses for all events showed a top-down saturation mechanism, which led to the formation of a saturated face with a maximum thickness of 5 m. Stability analyses conducted for the same events showed the development of a shallow landslide in the first few metres of saturated soil. The modelling results are compatible with the actual evolution of the phenomenon and allow us to understand the triggering mechanism, providing models to support future interventions. [ABSTRACT FROM AUTHOR]

In this work, we apply a physically based model, namely the HIRESSS (HIgh REsolution Slope Stability Simulator) model, to forecast the occurrence of shallow landslides at the regional scale. HIRESSS is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions during a rainfall event. The modeling software is made up of two parts: hydrological and geotechnical. The hydrological model is based on an analytical solution from an approximated form of the Richards equation, while the geotechnical stability model is based on an infinite slope model that takes the unsaturated soil condition into account. The test area is a portion of the Aosta Valley region, located in the northwest of the Alpine mountain chain. The geomorphology of the region is characterized by steep slopes with elevations ranging from 400ma.s.l. on the Dora Baltea River's floodplain to 4810ma.s.l. at Mont Blanc. In the study area, the mean annual precipitation is about 800-900 mm. These features make the territory very prone to landslides, mainly shallow rapid landslides and rockfalls. In order to apply the model and to increase its reliability, an in-depth study of the geotechnical and hydrological properties of hillslopes controlling shallow landslide formation was conducted. In particular, two campaigns of on site measurements and laboratory experiments were performed using 12 survey points. The data collected contributed to the generation of an input map of parameters for the HIRESSS model. In order to consider the effect of vegetation on slope stability, the soil reinforcement due to the presence of roots was also taken into account; this was done based on vegetation maps and literature values of root cohesion. The model was applied using back analysis for two past events that affected the Aosta Valley region between 2008 and 2009, triggering several fast shallow landslides. The validation of the results, carried out using a database of past landslides, provided good results and a good prediction accuracy for the HIRESSS model from both a temporal and spatial point of view. [ABSTRACT FROM AUTHOR]

In this work, we apply a physically-based model, namely the HIRESSS (High REsolution Stability Simulator) model, to forecast the occurrence of shallow landslides at regional scale. The final aim is the set-up of an early warning system at regional scale for shallow landslides. HIRESSS is a physically based distributed slope stability simulator for analysing shallow landslide triggering conditions in real time and in large areas using parallel computational techniques. The software can run in real-time by assimilating weather data and uses Monte Carlo simulation techniques to manage the geotechnical and hydrological input parameters. The test area is a portion of the Valle d'Aosta region, located in North-West Alpine mountain chain. The geomorphology of the region is characterized by steep slopes with elevations ranging from 400ma.s.l. of Dora Baltea's river floodplain to 4810ma.s.l. of Mont Blanc. In the study area, the mean annual precipitation is about 800-900mm. These features lead to a high hydrogeological hazard in the whole territory, as mass movements interest the 70% of the municipality areas (mainly shallow rapid landslides and rock falls). In order to apply the model and to increase its reliability, an in-depth study of the geotechnical and hydrological properties of hillslopes controlling shallow landslides formation was conducted. In particular, two campaigns of on site measurements and laboratory experiments were performed with 12 survey points. The data collected contributes to generate input map of parameters for HIRESSS model. In order to take into account the effect of vegetation on slope stability, the contribution of the root cohesion has been also taken into account based on the vegetation map and literature values. The model was applied in back analysis on two past events that have affected Valle d'Aosta region between 2008 and 2009, triggering several fast shallow landslides. The validation of the results, carried out using a database of past landslides, has provided good results and a good prediction accuracy of the HIRESSS model both from temporal and spatial point of view. A statistical analysis of the HIRESSS outputs in terms of failure probability has been carried out in order to define reliable alert levels for regional landslide early warning systems. [ABSTRACT FROM AUTHOR]

Distributed physically based slope stability models usually provide outputs representing, on a pixel basis, the probability of failure of each cell. This kind of result, although scientifically sound, from an operational point of view has several limitations. First, the procedure of validation lacks standards. As instance, it is not straightforward to decide above which percentage of failure probability a pixel (or larger spatial units) should be considered unstable. Second, the validation procedure is a time-consuming task, usually requiring a long series of GIS operations to overlap landslide inventories and model outputs to extract statistically significant performance metrics. Finally, if model outputs are conceived to be used in the operational management of landslide hazard (e.g., early warning procedures), the pixeled probabilistic output is difficult to handle and a synthesis to characterize the hazard scenario over larger spatial units is usually required to issue warnings aimed at specific operational procedures. In this work, a tool is presented that automates the validation procedure for physically based distributed probabilistic slope stability models and translates the pixeled outputs in warnings released over larger spatial units like small watersheds. The tool is named DTVT (double-threshold validation tool) because it defines a warning criterion on the basis of two threshold values—the probability of failure above which a pixel should be considered stable (failure probability threshold, FPT) and the percentage of unstable pixels needed in each watershed to consider the hazard level widespread enough to justify the issuing of an alert (instability diffusion threshold, IDT). A series of GIS operations were organized in a model builder to reaggregate the raw instability maps from pixels to watershed; draw the warning maps; compare them with an existing landslide inventory; build a contingency matrix counting true positives, true negatives, false positive, and false negatives; and draw in a map the results of the validation. The DTVT tool was tested in an alert zone of the Aosta Valley (northern Italy) to investigate the high sensitivity of the results to the values selected for the two thresholds. Moreover, among 24 different configurations tested, we performed a quantitative comparison to identify which criterion (in the case of our study, there was an 85% or higher failure probability in 5% or more of the pixels of a watershed) produces the most reliable validation results, thus appearing as the most promising candidate to be used to issue alerts during civil protection warning activities. [ABSTRACT FROM AUTHOR]

The influence of vegetation on mechanical and hydrological soil behavior represents a significant factor to be considered in shallow landslides modelling. Among the multiple effects exerted by vegetation, root reinforcement is widely recognized as one of the most relevant for slope stability. Lately, the literature has been greatly enriched by novel research on this phenomenon. To investigate which aspects have been most treated, which results have been obtained and which aspects require further attention, we reviewed papers published during the period of 2015–2020 dealing with root reinforcement. This paper—after introducing main effects of vegetation on slope stability, recalling studies of reference—provides a synthesis of the main contributions to the subtopics: (i) approaches for estimating root reinforcement distribution at a regional scale; (ii) new slope stability models, including root reinforcement and (iii) the influence of particular plant species, forest management, forest structure, wildfires and soil moisture gradient on root reinforcement. Including root reinforcement in slope stability analysis has resulted a topic receiving growing attention, particularly in Europe; in addition, research interests are also emerging in Asia. Despite recent advances, including root reinforcement into regional models still represents a research challenge, because of its high spatial and temporal variability: only a few applications are reported about areas of hundreds of square kilometers. The most promising and necessary future research directions include the study of soil moisture gradient and wildfire controls on the root strength, as these aspects have not been fully integrated into slope stability modelling. [ABSTRACT FROM AUTHOR]

Vegetation plays a crucial role in slope stability affecting soil behaviour through many hydrological and mechanical processes. At the catchment scale, the hydrological effects of interception, suction, evapotranspiration and infiltration strongly affect runoff processes, whilst at the local scale the mechanical effect of root reinforcement is the leading factor for slope stability. Root systems of plants increase the shear strength of soils through a combined action by the large and the small roots: large woody roots can anchor the superficial soil layers to more stable substrates crossing potential planes of weakness; small roots strengthen the bounds with the soil particles increasing the overall cohesion of the matrix soil-roots. The belowground conditions that determine the root reinforcement are extremely variable, so that field measurements of the additional cohesion provided by roots can vary by an order of magnitude even for plants of same species and age. The extreme variability of this parameter coupled to the practical difficulties in assessing its spatial variations, especially for large areas, represent a significant limit in including proper values of root cohesion in slope stability models.In this study we analysed the effect of the roots cohesion on slope stability simulations obtained using the HIRESSS model. HIRESSS is a physically based distributed slope stability simulator developed to provide results in near real time and for large areas. For the latest version, the simulator was modified to insert the root reinforcement among the geotechnical parameters that considers to compute the factor of safety in probabilistic terms. A comparison of the results between two different simulations was performed: considering a large area (900 km2) and 30 days of precipitations, in one case the root cohesion was set to zero for all the area, in the other case different values of the parameter based on the plant species was instead inserted in the model.To build a map of the root cohesion for the study area, the following solution was adopted to solve the problem of the evaluation of the parameter: the distribution of plant species in the area was obtained from CORINE land cover 2012 4th level map, then a value of root cohesion and a range of variation was defined for each plant species based on the most recent literature in this field, finally, to reproduce the natural variability, the root reinforcement was treated as variable in Monte Carlo simulations, as well as the other geotechnical parameters.The results of the simulations for the study area were processed and analysed in order to evaluate the effect of root cohesion on failure probabilities. The results were also analysed considering landslide actual events to assess the contribution of the parameter to the HIRESSS forecasting capabilities. [ABSTRACT FROM AUTHOR]