Abstract Detecting, locating, and characterising the dynamics of destabilised volcanic material is critical for assessing the extreme hazards posed by volcanic mass flows, such as pyroclastic density currents. Geophysical measurements of these events may offer information otherwise hardly observable at close range. Here we investigate pyroclastic density current dynamics using a multiparameter approach that combines seismic, distributed acoustic sensing, and infrasound data with thermal and visible imagery, supported by numerical simulations. We focus on two events at Stromboli volcano, Italy, that occurred in October and December 2022. By comparing visible imagery with seismic energy and applying array processing techniques, we identify different flow volumes ( ~23.5 ± 9.5 × 10 3 m 3 and ~80 ± 9 × 10 3 m 3 , respectively) and velocities (33-42 m/s and 54-59 m/s, respectively). Simulations reveal that reproducing these velocities requires volume-dependent empirical friction angles ( ~27° and 21°), consistent with dry granular flow behaviour and friction weakening. These findings offer new insights into the use of distributed acoustic sensing for volcanic monitoring and underscore the value of integrating multiparameter data with modeling to better understand complex volcanic processes.
Biagioli et al. (Thu,) studied this question.