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The analysis of slope stability over large areas is a demanding task for several reasons, such as the need for extensive datasets, the uncertainty of collected data, the difficulty of accounting for site-specific factors, and the considerable computation time required due to the size of investigated areas, which can pose major barriers, particularly in civil protection contexts where rapid analysis and forecasts are essential. However, as the identification of zones of higher failure probability is very useful for stakeholders and decision-makers, the scientific community has attempted to improve capabilities to provide physically based assessments. This study combined a transient seepage analysis of an unsaturated-saturated condition with an infinite slope stability model and probabilistic analysis through the use of a high-computing capacity parallelized platform. Both short- and long-term analyses were performed for a study area, and roles of evapotranspiration, vegetation interception, and the root increment of soil strength were considered. A model was first calibrated based on hourly rainfall data recorded over a 4-day event (December 14–17, 1999) causing destructive landslides to compare the results of model simulations to actual landslide events. Then, the calibrated model was applied for a long-term simulation where daily rainfall data recorded over a 4-year period (January 1, 2005–December 31, 2008) were considered to study the behavior of the area in response to a long period of rainfall. The calibration shows that the model can correctly identify higher failure probability within the time range of the observed landslides as well as the extents and locations of zones computed as the most prone ones. The long-term analysis allowed for the identification of a number of days (9) when the slope factor of safety was lower than 1.2 over a significant number of cells. In all of these cases, zones approaching slope instability were concentrated in specific sectors and catchments of the study area. In addition, some subbasins were found to be the most recurrently prone to possible slope instability. Interestingly, the application of the adopted methodology provided clear indications of both weekly and seasonal fluctuations of overall slope stability conditions. Limitations of the present study and future developments are finally discussed. [ABSTRACT FROM AUTHOR]

• Regional distributed stability modelling integrating the root reinforcement effect. • Long simulations considering regional hourly rainfall of one-month periods. • Root cohesion regional changes by species distribution and Monte Carlo simulations. • Minor influence of the root reinforcement when soil conditions are near saturation. We present a regionally distributed slope stability modelling for shallow landslides considering the effect of plant roots. Our modelling is based on the physically-based distributed slope stability model, HIRESSS (HIgh REsolution Slope Stability Simulator). Thanks to the parallel structure, our code is well suited to perform fast assessment of slope stability over large spatial and temporal scales. The reinforcing effect of plant roots is implemented into the code by considering the local plant species and their spatial variations. The probabilistic nature of the stability of slopes is considered by performing Monte Carlo simulations. Our model is applied to two study areas in Italy. The numerical results are compared with the collected data from these areas. The model predictions show that the effect of plant root is sensitive to rainfall intensity and duration. Our model prediction shows only minor influence of plant root on slope stability particularly for the soil conditions near saturation. [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]