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Understanding the dynamics of slope instabilities is critical to mitigate the associated hazards, but their direct observation is often difficult due to their remote locations and their spontaneous nature. Seismology allows us to get unique information on these events, including on their dynamics. However, the link between the properties of these events (mass and kinematics) and the seismic signals generated is still poorly understood. We conducted a controlled rockfall experiment in the Riou Bourdoux torrent (southern French Alps) to try to better decipher those links. We deployed a dense seismic network and inferred the dynamics of the block from the reconstruction of the 3D trajectory from terrestrial and airborne high-resolution stereophotogrammetry. We propose a new approach based on machine learning to predict the mass and the velocity of each block. Our results show that we can predict those quantities with average errors of approximately 10 % for the velocity and 25 % for the mass. These accuracies are as good as or better than those obtained by other approaches, but our approach has the advantage in that it does not require the source to be localised, nor does it require a high-resolution velocity model or a strong assumption on the seismic wave attenuation model. Finally, the machine learning approach allows us to explore more widely the correlations between the features of the seismic signal generated by the rockfalls and their physical properties, and it might eventually lead to better constraints on the physical models in the future. [ABSTRACT FROM AUTHOR]

In mountainous regions, global warming will likely affect the frequency and magnitude of geomorphic processes. This is also the case for rockfall, one of the most common mass movements on steep slopes. Rainfall, snowmelt, or freeze-thaw cycles are the main drivers of rockfall activity, rockfall hazards are thus generally thought to become more relevant in a context of climate change. At high elevations, unequivocal relationships have been found between increased rockfall activity, permafrost thawing and global warming. By contrast, below the permafrost limit, studies are scarcer. They mostly rely on short or incomplete rockfall records, and have so far failed to identify climatically induced trends in rockfall records. Here, using a dendrogeomorphic approach, we develop two continuous 60-year long chronologies of rockfall activity in the Vercors and Diois massifs (French Alps); both sites are located clearly below the permafrost limit. Uncertainties related to the decreasing number of trees available back in time were quantified based on a detailed mapping of trees covering the slope across time. Significant multiple regression models with reconstructed rockfalls as predictors and local changes in climatic conditions since 1959 extracted from the SAFRAN reanalysis dataset as predictants were fitted to investigate the potential impacts of global warming on rockfall activity at both sites. In the Vercors massif, the strong increase in reconstructed rockfall can be ascribed to the recolonization of the forest stand and the over-representation of young trees; changes that are observed should not therefore be ascribed to climatic fluctuations. In the Diois massif, we identify annual precipitation totals and mean temperatures as statistically significant drivers of rockfall activity but no significant increasing trend was identified in the reconstruction. All in all, despite the stringency of our approach, we cannot therefore confirm that rockfall hazard will increase as a result of global warming at our sites. [ABSTRACT FROM AUTHOR]

The spatial and temporal quantification of rockfall frequency remains a major challenge in mountain environments, especially also in terms of rockfall management. Approaches that have been used traditionally to quantify rockfall frequency include historical records, remote sensing, or in situ monitoring, but have been shown repeatedly to suffer from a lack of completeness or to rely on rather short time series (of a few years) that are, in addition, limited to small areas. As such, they normally cannot meet the stringent requirements of hazard and risk analyses. Here, we propose a new procedure coupling field analysis of rockfall deposits in mitigation structures and growth disturbances in tree-ring series with three-dimensional (3D), process-based rockfall modeling to estimate rockfall frequencies for individual cliff compartments. This procedure has been tested on a slope in the Swiss Alps (La Fory, Sembrancher VS), where rockfall triggered from a 38 hm2 cliff to threaten a 1-km-long section of the road to the Grand St. Bernard tunnel and the local railway line. Based on 84 rockfall deposits retrieved from 420-m-long protection barrier and growth disturbances in trees over the 1994–2017 period, we estimate rockfall hazard to between 0.043 and 0.348 events yr–1 at various locations on the slope. In total, we used 68,680,000 rockfall simulations to translate hazard values into rockfall frequencies at the cliff level. Converging release frequencies between tree-ring analyses (0.99–1.35 events yr–1 hm–2) and values obtained from deposits in the protection barrier (0.82 events yr–1 hm–2) confirm the reliability of our procedure. Despite remaining limitations, our approach enables precise quantification of rockfall release frequency in a holistic and reproducible manner both in space (a few hm2) and time (several decades), and thus yields the data needed for hazard and risk mapping. We therefore recommend, where applicable, to include this procedure in future rockfall management strategies. [ABSTRACT FROM AUTHOR]

• Hydrological and mechanical reinforcement from vegetation was assessed. • Roots in high elevation forests are slow to recover after soil disturbance. • Roots in gaps in low elevation forests recover quickly after soil disturbance. • Hydrological reinforcement fluctuates more strongly with season than mechanical reinforcement. • Mechanical reinforcement is more reliable than hydrological reinforcement. Natural hazards such as shallow landslides are common phenomena that disturb soil and damage forests. Quantifying the recovery of forest vegetation after a hazard is important for determining the window of susceptibility to new disturbance events, especially at high elevations, where extreme weather events are frequent and the growing season is short. Plant roots can reduce the size of this window on unstable hillslopes, by adding mechanical reinforcement (c r) to soil and increasing its matric suction, termed here as hydrological reinforcement (c h). These data are used in landslide models to calculate the Factor of Safety (FoS) of a hillslope. We calculated temporal variations in c r and c h in naturally regenerated mixed, montane forests in the French Alps. In these closed-canopy forests, open-canopy gaps were present, with understory vegetation comprising herbs, forbs and shrubs. At three altitudes (1400, 1700 and 2000 m), we dug small trenches as proxies for shallow landslide events and calculated c r before soil disturbance in both open gaps and closed forests. Then, using monthly tree root initiation and mortality data measured in rhizotrons, we calculated monthly c r for four years after the disturbance. To compare results with c r , c h was estimated using matric suction data that were measured in trenches at 1400 m for >1 year. Temporal FoS was then calculated using an infinite slope stability model. Results showed that finer, short-lived roots contributed little to soil reinforcement compared to thicker, long-lived roots. After disturbance, mean c r (over the entire soil profile) never fully recovered to the initial value at any site, although >90% recovery was observed in open gaps at 1400 m. Mean c r was slow to recover in closed forests, especially at 2000 m, where only 19% recovery occurred after 41 months. The c h in closed forests was considerable during the summer months, but marked increases in soil water moisture resulted in lower FoS, especially during December to April, when soil was near saturation. As c r changed little throughout the year, it was a more reliable contributor to slope stability. Our results show therefore, that particular attention should be paid to high elevation forests after a disturbance. Also, during the process of recovery, the highly variable soil water dynamics in closed forest can result in seasonal hotspots of vulnerability. Therefore, when tree transpiration is low, our results highlight a need for careful monitoring on steep or unstable slopes, especially in disturbed closed-canopy forests. [ABSTRACT FROM AUTHOR]