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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]

Synthetic Aperture Radar (SAR) acquisition can be performed from satellites or from the ground by means of a so- called GB-InSAR (Ground-Based Interferometry SAR), but the signal emission and the output image geometry slightly differ between the two acquisition modes. Those differences are rarely mentioned in the literature. This paper proposes to compare satellite and GB-InSAR in terms of (1) acquisition characteristics and parameters to consider; (2) SAR image resolution; (3) geometric distortions that are foreshortening, layover and shadowing. If in the case of satellites SAR, the range and azimuth resolutions are known and constant along the orbit path, in the case of GB-InSAR their values are terrain-dependent. It is worth estimating the results of a GB-InSAR acquisition one can expect in terms of range and azimuth resolution, Line of Sight (LoS) distance and geometric distortions to select the best installation location when several are possible. We developed a tool which estimates those parameters from a Digital Elevation Model (DEM), knowing the GB-InSAR and the Slope of Interest (Sol) coordinates. This tool, written in MATLAB, was tested on a simple synthetic point cloud representing a cliff with a progressive slope angle to highlight the influence of the Sol geometry on the acquisition characteristics and on two real cases; cliffs located in Switzerland, one in the Ticino canton and on in the Vaud canton. [ABSTRACT FROM AUTHOR]

Foreseeing the failure of important unstable volumes is a major concern in the Alps, especially due to the presence of people and infrastructures in the valleys. The use of monitoring and remote sensing techniques is aimed at detecting potential instabilities and the combination of several techniques permits the cross-validation of the detected movements. Supplemented with field mapping and structural analysis, it is possible to define possible scenarios of rupture in terms of volume, mechanisms of failure and susceptibility. A combined observation strategy was applied to the study of major instability located in the Ticinese Alps (Switzerland), Cima del Simano, where the monitoring started in 2006 with the measurement of opened cracks with extensometers. Since 2021, the monitoring has been completed by LiDAR, satellite and GB-InSAR observations and structural analysis. Here, slow but constant movements of about 7 mm/yr were detected along with rockfall activities near the Simano summit. Eight failure scenarios of various sizes ranging from 2.3 × 105 m3 to 51 × 106 m3, various mechanisms (toppling, planar, wedge and circular sliding) and various occurrence probabilities were defined based on the topography and the monitoring results and by applying a Slope Local Base Level (SLBL) algorithm. Weather acquisition campaigns by means of thermologgers were also conducted to suggest possible causes that lead to the observed movements and to suggest the evolution of the instabilities with actual and future climate changes. [ABSTRACT FROM AUTHOR]

The reliable in situ quantification of rock mass fracturing and engineering quality is critical for slope stability, surface mining and rock engineering applications, yet it remains difficult due to the heterogeneous nature of fracture networks. We propose a method to quantify and map the slope-scale geomechanical quality of fractured rock masses using infrared thermography (IRT). We use the Mt. Gorsa quarry (Trentino, Italy) as a field laboratory to upscale a physics-based approach, which was developed in the laboratory, to in situ conditions, including the effects of fracture heterogeneity, environmental conditions and IRT limitations. We reconstructed the slope in 3D using UAV photogrammetry, characterized the rock mass quality in the field at selected outcrops in terms of the Geological Strength Index (GSI) and measured their cooling behavior through 18h time-lapse IRT surveys. With ad hoc field experiments, we developed a novel procedure to correct IRT data in outdoor environments with complex topography. This allowed for a spatially distributed quantification of the rock mass surface cooling behavior in terms of a Curve Shape Parameter (CSP). Using non-linear regression, we established a quantitative CSP-GSI relationship, which allowed for the CSP to be translated into GSI maps. Our results demonstrate the possibility of applying infrared thermography to the slope-scale mapping of rock mass fracturing based on a physics-based experimental methodology. [ABSTRACT FROM AUTHOR]

Rockfall simulations are often performed at various levels of detail depending on the required safety margins of rockfall-hazard-related assessments. As a pseudo benchmark, the simulation results from different models can be put side-by-side and compared with reconstructed rockfall trajectories, and mapped deposited block fragments from real events. This allows for assessing the objectivity, predictability, and sensitivity of the models. For this exercise, mapped data of past events from the Mel de la Niva site are used in this paper for a qualitative comparison with simulation results obtained from early calibration stages of the Flow-R 2.0.9, Rockyfor3D 5.2.15 and RAMMS::ROCKFALL 1.6.70 software. The large block fragments, reaching hundreds of megajoules during their fall, greatly exceed the rockfall energies of the empirical databases used for the development of most rockfall models. The comparison for this challenging site shows that the models could be improved and that combining the use of software programs with different behaviors could be a workaround in the interim. The findings also highlight the inconvenient importance of calibrating the simulations on a per-site basis from onsite observations. To complement this process, a back calculation tool is briefly described and provided. This work also emphasizes the need to better understand rockfall dynamics to help improve rebound models. [ABSTRACT FROM AUTHOR]

This research paper presents a comprehensive approach to investigating dry granular collapses in three dimensions, by combining analytical, numerical, and experimental methods. The experimental investigation utilised a novel apparatus to study granular collapses in the laboratory. It is demonstrated that a quasistatic understanding of granular collapses can accurately predict the final normalised run-out distances for dynamic granular collapses. Our approach involved establishing a correlation between the angle of repose and the initial aspect ratio of the granular column. It is also shown that the material point method (MPM) is suitable for modelling granular collapses in three dimensions. Our in-house solver was further validated using experimental evidence under an explicit formulation, resulting in good agreement between the numerical and experimental results. The findings demonstrate the effectiveness of our in-house solver for three-dimensional granular collapse modelling. [ABSTRACT FROM AUTHOR]

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