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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]

Over large regions exposed to natural disasters, cascading effects resulting from complex or concatenated natural processes may represent a large portion of total risk. Populated high‐mountain environments are a major concern, and methods for large‐scale quantitative risk analyses are urgently required to improve risk mitigation. This article presents a comprehensive quantitative rockfall risk assessment over a large archetypal valley of the Andean mountains, in Central Chile, which integrates a wide spectrum of elements at risk. Risk is expressed as an expected damage both in monetary terms and casualties, at different scales relevant for decision making. Notably, total rockfall risk is divided into its main drivers, which allows quantifying seismically induced rockfall risk. For this purpose, the local seismic hazard is quantified and the yield acceleration, that is, acceleration required to initiate rockfall, is determined at the regional scale. The probability of failure is thereafter derived in terms of annual frequency of rockfall initiation and integrated in the quantitative risk assessment (QRA) process. Our results show the significant role of seismic activity as the triggering mechanism of rockfalls, and highlight elements at risk that have a major contribution to the total risk. Eventually a sensitivity analysis is conducted to (i) assess the robustness of obtained risk estimates to the data and modeling choices and (ii) identify the most influential assumptions. Our approach evidences the feasibility of large‐scale QRAs in sensitive environments and opens perspectives for refining QRAs in similar territories significantly affected by cascading effects and multihazards. [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 use of dynamic computational methods has become indispensable for addressing problems related to rockfall hazard. Although a number of models with various degrees of complexity are available, model parameters are rarely calibrated against observations from rockfall experiments. A major difficulty lies in reproducing the apparent randomness of the impact process related to both ground and block irregularities. Calibration of rigorous methods capable of explicitly modeling trajectories and impact physics of irregular blocks is difficult, as parameter spaces become too vast and the quality of model input and observation data are insufficient. The model presented here returns to the simple 'lumped-mass' approach and simulates the characteristic randomness of rockfall impact as a stochastic process. Despite similarities to existing approaches, the model presented here incorporates several novel concepts: (i) ground roughness and particle roughness are represented as a random change of slope angle at impact; (ii) lateral deviations of rebound direction from the trajectory plane at impact are similarly accounted for by perturbing the ground orientation laterally, thus inducing scatter of run-out directions; and (iii) a hyperbolic relationship connects restitution factors to impact deformation energy. With these features, the model is capable of realistically accounting for the influence of particle mass on dynamic behaviour. The model only requires four input parameters, rendering it flexible for calibration against observed datasets. In this study, we calibrate the model against observations from the rockfall test site at Vaujany in France. The model is able to reproduce observed distributions of velocity, jump heights, and runout at observation points. In addition, the spatial distribution of the trajectories and landing points has been successfully simulated. Different parameter sets have been used for different ground materials such as an avalanche channel, a forest road, and a talus cone. Further calibration of the new model against a range of field datasets is essential. This study is part of an extensive calibration program that is still in progress at this first presentation of the method, and focuses on fine-tuning the details of the stochastic process implemented both in two-dimensional (2D) and three-dimensional (3D) versions of the model. Key words: rockfall, run-out simulation, stochastic methods. Il est devenu indispensable d'utiliser des methodes de calcul dynamiques pour resoudre des problemes lies aux risques d'eboulement. Bien qu'il existe actuellement un grand nombre de modeles aux degres de complexite varies, les parametres de ces modeles sont rarement ajustes en fonction des observations faites lors d'experiences d'eboulements. Une difficulte majeure reside dans la reproduction du caractere apparemment aleatoire du processus d'impact des particules, lequel est lie aux irregularites des sols et blocs rocheux. Il est difficile de calibrer des methodes rigoureuses capables de modeliser clairement les trajectoires et impacts de blocs irreguliers d'un point de vue physique, etant donne que l'etendue des parametres devient trop importante et que la qualite des donnees d'observation et de celles entrees dans le modele est insuffisante. Le modele presente ici revient a l'approche simplifiee de la << masse unique >> et simule le caractere typiquement aleatoire de l'impact des pierres lors de l'eboulement sous forme d'un processus stochastique. Malgre les similitudes avec les approches existantes, le modele presente inclue plusieurs concepts novateurs : (i) la rugosite du sol et des particules est representee apparait comme etant une variation aleatoire de l'inclinaison de la pente lors de l'impact; (ii) les deviations laterales de la direction dans laquelle rebondissent les particules par rapport au plan de leur trajectoire lors de l'impact s'expliquent par la variation d'inclinaison du sol sur les cotes, ce qui provoque un eparpillement des particules dans toutes les directions; et (iii) une relation hyperbolique existe entre les facteurs de restitution et l'energie de deformation a l'impact. Grace a ces caracteristiques, le modele est en mesure d'expliquer de maniere realiste l'influence de la masse des particules sur la dynamique de l'eboulement. Du fait qu'il ne requiert que quatre parametres de depart, le modele est a calibrer en fonction des ensembles de donnees recueillies. Dans la presente etude, nous calibrons le modele en fonction d'observations faites sur le site de Vaujany, en France, ou l'on procede a des essais d'eboulement. Grace a ce modele, il est possible d'obtenir les memes courbes de distribution des vitesses et les memes hauteurs et trajectoires de projection des particules que celles observees a divers endroits sur le terrain. En outre, on a reussi a simuler la distribution spatiale des trajectoires et destinations des particules. Differents groupes de parametres ont ete utilises divers types de terrains tels qu'un canal d'avalanche, une route forestiere et un cone d'eboulis. Il est indispensable d'effectuer une calibration plus poussee du nouveau modele en fonction d'un large eventail de donnees collectees sur le terrain. La presente etude s'integre dans un programme de calibration poussee, toujours en cours au moment oU l'on presente le nouveau modele pour la premiere fois, et a pour objectif de preciser les details du processus stochastique mis en pratique dans les versions bidimensionnelle (2D) et tridimensionnel (3D) du modele. [Traduit par la Redaction] Mots-cles : eboulement, simulation des trajectoires de projection, methodes stochastiques., Introduction Rockfall is a type of landslide consisting of detachment, fall, rolling, and bouncing of rock fragments (Hungr et al. 2014). It may occur as single events or in clusters, [...]