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The stability and erosion of natural and man-made slopes is influenced by soil-vegetation-atmosphere interactions and the thermo-hydro-mechanical slope conditions. Understanding such interactions at the source of slope mass-wasting is important to develop land-use planning strategy and to promote environmentally adapted mitigation strategies, such as the use of vegetation to stabilize slopes and control erosion. Monitoring is essential for calibrating and validating models and for better comprehending the physical mechanisms of soil-vegetation-atmosphere interactions. We approached this complex problem by means of an experimental work in a full-scale monitored embankment, which is divided into four instrumented partitions. These partitions are North or South-faced and present a bare and vegetation cover at each orientation. Our main findings show that vegetation enhances rainfall infiltration and decreases runoff, which reduces slope stability and surficial erosion, while plant transpiration induces higher suctions and hence slope stability. Concerning thermal aspects, vegetation reduces the incidence of net solar radiation and consequently heat flux. Thus, daily temperature fluctuations and evaporation decreases. However, the effect of vegetation in the development of dryer soil conditions is more significant than the orientation effect, presenting higher drying rates and states at the North-vegetated slope compared to the South-bare slope. [ABSTRACT FROM AUTHOR]

Slope mass-wasting like shallow slides are mostly triggered by climate effects, such as rainfall, and soil–vegetation–atmosphere (SVA) interactions play a key role. SVA interactions are studied by a full-scale embankment with different orientations (North and South) and vegetation covers (bare and vegetated) in the framework of the prediction of climate change effects on slope stability in the Pyrenees. A clayey sand from the Llobregat river delta was used for the construction of the embankment and laboratory tests showed the importance of suction on the strength and hydraulic conductivity. Sixty sensors, which are mostly installed at the upper soil layer of the embankment, registered 122 variables at four vertical profiles and the meteorological station with a 5 min scan rate. Regarding temperature, daily temperature fluctuation at the shallow soil layer disappeared at a depth of about 0.5 m. There was great influence of orientation with much higher values at the South-facing slope (up to 55 °C at −1 cm depth) due to solar radiation. Regarding rainfall infiltration, only long duration rainfalls produced an important increase of soil moisture and pore water pressure, while short duration rainfalls did not trigger significant variations. However, these changes mostly affected the surface soil layer and decreased with depth. [ABSTRACT FROM AUTHOR]

• A fast physically-based model for regional landslide susceptibility assessment. • Both lateral and vertical flows were considered to calculate the water table. • Stochastic approach for the input parameters cohesion and friction angle. • Model application by using landslide inventory in Andorra, Pyrenees. • Very short computational time (~2 min) to calculate a large area (~479 km2). Rainfall-induced landslides represent an important threat in mountainous areas. Therefore, a physically-based model called "Fast Shallow Landslide Assessment Model" (FSLAM) was developed to calculate large areas (>100 km2) with a high-resolution topography in a very short computational time. FSLAM applies a simplified hydrological model and the infinite slope theory, while the two most sensitive soil properties regarding slope stability (cohesion and friction angle) can be stochastically included. The model has five necessary input raster files including information of soil properties, vegetation, elevation and rainfall. The principal output is the probability of failure (PoF) map. The Principality of Andorra was selected as case study, where FSLAM was successfully applied and validated using the existing landslide inventory. The PoF raster file of Andorra (including 19 million cells) was calculated in only 2 min. Therefore, an accurate calibration of the input parameters was easy, which strongly improved the final outcomes. [ABSTRACT FROM AUTHOR]