Between December 2020 and February 2022, the South East Crater of Etna has been the source of numerous eruptions, mostly characterized by the emission of lava fountains, pyroclastic material and short-lasting lava flows. Here we estimate the volume and distribution of the lava deposits by elaborating multi-source satellite imagery. SEVIRI data have been elaborated using CL-HOTSAT to estimate the lava volume emitted during each event and calculate the cumulative volume; Pléiades and WorldView-1 data have been used to derive Digital Surface Models, whose differences provide thickness distributions and hence volumes of the volcanic deposits. We find a good agreement, with the total average lava volume obtained by SEVIRI reaching 73.2 × 10⁶ m³ and the one from optical data amounting to 67.7 × 10⁶ m³. This proves the robustness of both techniques and the accuracy of the volume estimates, which provide important information on the lava flooding history and evolution of the volcano.

The rate at which lava is discharged plays a key role in controlling the distance covered by lava flows from eruptive vents. We investigate the available time-averaged discharge rates (TADRs) estimated for recent flank eruptions at Mt. Etna volcano (Italy), in order to define a possible generalized effusion rate trend which is consistent with observed real data. Our analysis indicates a rapid waxing phase in which effusion rate peaks occur for between 0.5 and 29% of the total eruption time, followed by a progressive decrease in the waning phase. Three generalized curves are built by calculating the 25th, 50th and 75th percentiles values associated with the occurrence of effusion peaks, and with the slope variations of descending curves in the waning phase. The obtained curves are used as an input for the GPUFLOW model in order to perform numerical simulations of the lava flows paths on inclined planes, and are compared with those generated by using effusion rate curves with a bell-shaped time-distribution. Our tests show how these characteristic curves could impact single-vent scenarios, as well as short- and long-term hazard maps, with maximum variations of up to 40% for a specific category of eruptive events.

The development of probabilistic maps associated with lava flow inundation is essential to assess hazard in open vent volcanoes, especially those that have highly urbanized flanks. In this study we present the new lava flow hazard map linked to the summit eruptions of Mt. Etna, which has been developed using a probabilistic approach that integrates statistical analyses of the volcanological historical data with numerical simulations of lava flows. The statistical analysis of volcanological data (including vent location, duration and lava volumes) about all summit eruptions occurred since 1998 has allowed us both to estimate the spatiotemporal probability of future vent opening and to extract the effusion rate curves for lava flow modelling. Numerical simulations were run using the GPUFLOW model on a 2022 Digital Surface Model derived from optical satellite images. The probabilistic approach has been validated through a back-analysis by calculating the fit between the expected probabilities of inundation and the lava flows actually emplaced during the 2020-2022 period. The obtained map shows a very high probability of inundation of lava flows emitted at vents linked to the South East Crater, according to the observation of the eruptive dynamics in the last decades.

We hereby present VolcFire, a new cellular automaton model for fire propagation aimed at the creation of fire hazard maps for fires of volcanic origin. The new model relies on satellite-derived input data for the topography, land-use, fuel, and humidity information, and produces probabilistic maps of fire propagation simulating fire spread. The model contains several simplifications compared to the current state-of-the-art, limiting its usability to plan fire-fighting interventions during an event in favour of a reduced computational load. The accuracy and reliability of the model are also discussed by presenting its ability to reproduce two recent fires on Stromboli island, with good spatial fit (Brier score of $0.146\pm 0.002$ for the 3 July 2019 volcanic fire, and of $0.073\pm 0.001$ for the 25 May 2022 anthropogenic fire) and less than $1.5\%$ variation across multiple simulations for the same event.

Pyroclastic density currents (PDCs) are among the deadliest manifestations of volcanic eruptions, commonly associated with volcanoes characterized by intermediate to felsic magma compositions and related to eruption column collapse, lateral blasts, or gravitational failures of lava-domes. However, even basaltic, small-moderate eruptions have recently generated potentially lethal PDCs. We analyzed the PDC from the lava fountain of 10 February 2022 at Mt. Etna’s South East Crater. We integrated field, remote sensing and petrological data on the PDC products, together with video-recordings of the eruptive activity and numerical modeling to evaluate its propagation dynamics. Our analysis suggests that hot, altered portions of steep volcanic edifices may collapse and remobilize large amounts of deposits, constituting precursors of highly mobile granular flows. Monitoring their pre-eruptive trigger conditions continuously is therefore crucial for a robust assessment of the potential hazard, especially in the proximal areas of very active basaltic volcanoes frequented by numerous tourists.