Abstract

Defining the relationship between volume and return period is critical when estimating the risk of rockfalls and/or rock avalanche, especially during continued global warming at high altitudes that threatens rock wall stability. Characterizing the volume-frequency relationship based on historical datasets is, however, limited by observation and quantification biases, which have not received enough attention. Here, to monitor recent activities for the Brenva Spur (Mont-Blanc massif, Italy) that is also a rock avalanche scar and estimate the return period of future rock failures based on the volume-frequency relationship (and the corresponding uncertainty), a structure-from-motion photogrammetric survey was conducted from 2017 to 2021. 39 rockfall sources with volumes ranging from 11 to 13,250 m3 were identified within the scar. The total failure volume is 22,438 m3, with an associated erosion rate of 15.5 mm/year, indicating very active morphodynamics possibly linked to the permafrost evolution in the spur. The volumes were characterized by a negative power-law that fits significant two events in 2016 (3.4 × 104 m3) and one in 1997 (2.0 × 106 m3) remarkably well, and the randomness of the fit was evaluated by a Monte Carlo approach. 7 potential failure scenarios ranging from 3.1 × 104 m3 (S1) to 4.8 × 106 m3 (S7) were defined according to a structural analysis and the sloping local base level concept. Their extrapolated return periods derived by the power-law fit indicate a longer return period for the maximum failure scenario than for the smaller scenarios. S1 has a 50% chance of occurring every 3 years, while S7 has a 50% chance of occurring every 31 years. Though the median return period of S7 is 31 years, the 95% and 68.2% confidence intervals range from 8 to 399 years and 14 to 93 years, respectively, which reflects a high level of uncertainty but is realistic when considering global warming, progressive rock failure, etc. In addition to characterizing recent rock failure activities in high mountains, this study offers a preliminary examination of the return periods of some extreme scenarios and provides primary data for risk management in mountainous areas that are very sensitive to global warming.

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