Avalanche risk evaluation and protective dam optimal design using extreme value statistics

In snow avalanche long-term forecasting, existing risk-based methods remain difficult to use in a real engineering context. In this work, we expand a quasi analytical decisional model to obtain simple formulae to quantify risk and to perform the optimal design of an avalanche dam in a quick and efficient way. Specifically, the exponential runout model is replaced by the Generalized Pareto distribution (GPD), which has theoretical justifications that promote its use for modelling the different possible runout tail behaviours. Regarding the defence structure/flow interaction, a simple law based on kinetic energy dissipation is compared with a law based on the volume stored upstream of the dam, whose flexibility allows us to cope with various types of snow. We show how a detailed sensitivity study can be conducted, leading to intervals and bounds for risk estimates and optimal design values. Application to a typical case study from the French Alps, highlights potential operational difficulties and how they can be tackled. For instance, the highest sensitivity to the runout tail type and interaction law is found at abscissas of legal importance for hazard zoning (return periods of 10–1000 a), a crucial result for practical purposes.