Lagarde, Sophie ; Dietze, Michael ; Hammer, Conny ; Zeckra, Martin ; Voigtländer, Anne ; Illien, Luc ; Schöpa, Anne ; Hirschberg, Jacob ; Hovius, Niels ; Turowski, Jens M.

Talk presented at EGU General Assembly 2022, Vienna, Austria on 2022-05-23

Abstract: In order to reduce the societal impact of mass-wasting events, we need observations to investigate the factors that control slope failure, such as the state of crack propagation along a failure plane. However, usually the failure plane is not accessible in-situ. Hence, cracks have to be monitored indirectly, for example using seismic methods. We analysed the data from a seismometer array in the Illgraben catchment, Switzerland, that had registered a series of crack propagation and mass-wasting events, leading to a main event that happened on 2 January 2013. We used a state-of-the-art machine learning technique based on hidden Markov models to detect and classify the seismic signals of crack events. We obtained the temporal evolution of three signal types: (1) single crack signal, (2) rock avalanche and (3) rockfall activity due to debris remobilization. The temporal evolution of the number of cracks showed a linear trend in the weeks prior to the main mass-wasting event and, in the hours preceding the main event, a sigmoidal exponential growth. Using these observations, we propose a mechanistic model to describe the rupture of the failure plane. The model considers the internal parameter of the total crack boundary length as the primary control on failure plane evolution, in addition to the previously suggested crack propagation velocity control parameter. According to this model, internal parameters appear to be the dominant control for the failure plane growth at a slope scale.

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