Tree Blow‐Down by Snow Avalanche Air‐Blasts: Dynamic Magnification Effects and Turbulence

Snow avalanche‐induced air‐blasts are capable of breaking trees, damaging buildings and causing fatalities. Predicting their destructive properties is an essential part of snow avalanche hazard mitigation. Here, we propose a depth‐averaged model that involves turbulent fluctuations to simulate the air‐blast dynamics. The turbulent energy of the air‐blast arises from that of dust‐mixed air transferred from the avalanche core, shearing work in the cloud and entrained air, and is exploited to improve the air entrainment and drag relationships. We further present a unique data set of air blast‐induced tree breakage, providing type, status, diameter and falling direction of the measured trees. Through case studies of two artificially released avalanches with measured powder heights and three natural avalanches with tree‐breakage information, we test the model and investigate the turbulence effect on air‐blast dynamics. The proposed model and tree‐breakage data set quantify the air‐blast destructiveness and can be applied for avalanche hazard assessment. Snow avalanche‐induced air‐blasts are common natural hazards in high‐altitude regions. They are fully turbulent mixtures of ice dust and gases capable of causing damage and human fatalities far beyond the avalanche deposits, representing a major threat to societies in avalanche‐prone environments. In this study, we propose a robust numerical model that accounts for the turbulent fluctuations to simulate the air‐blast dynamics. An unprecedented data set of air blast‐induced tree breakage in three natural snow avalanches is further presented. Using five case studies in Switzerland, of which two artificial avalanches and three natural avalanches with tree‐breakage data, we test the model and investigate the impact of turbulence on air‐blast dynamics. Results suggest great performances of the proposed model in calculating the air‐blast height, impact area and dynamic pressure. Turbulent fluctuations play an important role in the travel resistance and air entrainment of the air‐blast, and can magnify the maximum pressure several times larger than the mean value. The new air‐blast hazard model gives promising perspectives for estimations of snow avalanche hazards, and the tree‐breakage data set can serve as a calibration basis for future more accurate numerical avalanche models. An unprecedented tree breakage data set is presented to quantify the magnitude and reach of the air‐blast generated by three snow avalanchesThe forest destruction is simulated with a depth‐averaged avalanche model to calculate the pressures induced by snow avalanche air‐blastsTurbulence can magnify the air‐blast pressure several times larger than the mean value, acting at frequencies near the tree frequencies An unprecedented tree breakage data set is presented to quantify the magnitude and reach of the air‐blast generated by three snow avalanches The forest destruction is simulated with a depth‐averaged avalanche model to calculate the pressures induced by snow avalanche air‐blasts Turbulence can magnify the air‐blast pressure several times larger than the mean value, acting at frequencies near the tree frequencies