Abstract
Abstract
Most snow avalanches occur unobserved, which becomes particularly dramatic when human lives are involved. Seismological observations can be helpful to unravel time and dynamics of unseen events, like the deadly avalanche of January 18, 2017, that hit a Resort-hotel at Rigopiano in the Abruzzi (Italy). Particle motion analysis and spectrograms from data recorded by a close seismic broadband station, calculation of synthetic seismograms, as well as simulation of the flow, allowed us to construct the dynamics of the snow avalanche that buried alive 40 people, killing 29. Due to the bad weather conditions, no visual observation was made, thus making it impossible to determine the exact moment of the avalanche and to report necessary observations of the dramatic event. On-site inspections revealed that the hotel was horizontally cut by shear forces and dislocated by 48 m in 70°N direction, once the increasing avalanche pressure exceeded the structural shear strength of the building. Within an eligible 24 min time range of the avalanche, we found three weak seismic transients, starting at 15:42:38 UTC, recorded by the nearest operating station GIGS located in the Gran Sasso underground laboratory approximately 17 km away. Particle motion analysis of the strongest seismic avalanche signal, as well as of the synthetic seismograms match best when assuming a single force seismic source, attacking in direction of 120°N. Simulation of the avalanche dynamics—calculated by using a 2D rapid mass movement simulator—indicates that the seismic signals were rather generated as the avalanche flowed through a narrow and twisting canyon directly above the hotel. Once the avalanche enters the canyon it is travelling at maximum velocity (37 m/s) and is twice strongly deflected by the rock sidewalls. These impacts created a distinct linearly polarized seismic “avalanche transient”s that can be used to time the destruction of the hotel. Our results demonstrate that seismic recordings combined with simulations of mass movements are indispensable to remotely monitor snow avalanches.
Publisher
Springer Science and Business Media LLC
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