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[1] Between 2007 and early 2008, the Istituto Nazionale di Geofisica e Vulcanologia (INGV) monitoring networks on Etna volcano recorded a recharging phase that climaxed with a new effusive eruption on 13 May 2008 and lasted about 14 months. A dike-forming intrusion was accompanied by a violent seismic swarm, with more than 230 events recorded in the first 6 h, the largest being M L = 3.9. In the meanwhile, marked ground deformation was recorded by the permanent tilt and GPS networks, and sudden changes in the summit area were detected by five continuously recording magnetic stations. Poor weather conditions did not allow direct observation of the eruptive events, but important information was provided by infrared satellite images that detected the start of lava fountains from the eruptive fissure, feeding a lava flow. This flow spread within the Valle del Bove depression, covering 6.4 km on the southeastern flank of the volcano in a few hours. The seismicity and deformation pattern indicated that the dike-forming intrusion was propagating northward. It produced a dry fracture field, which generated concern for the possibility that the eruptive fissures could expand downslope toward populated areas. Monitoring and modeling of the multidisciplinary data, together with the simulations of ash dispersal and lava flows, allowed us both to infer the eruptive mechanisms and to provide correct interpretation of the ongoing phenomena, furnishing useful information for civil defense purposes. We describe how this approach of feedback between monitoring and research provides critical support to risk evaluation.

Forecasting the lava flow invasion hazard in near‐real time is a primary challenge for volcano monitoring systems. The paroxysmal episode at Mount Etna on 12–13 January 2011 produced in ∼4 hours lava fountains and fast‐moving lava flows 4.3 km long. We produced timely predictions of the areas likely to be inundated by lava flows while the eruption was still ongoing. We employed infrared satellite data (MODIS, AVHRR, SEVIRI) to estimate in near‐real‐time lava eruption rates (peak value of 60 m3 s−1). These time‐varying discharge rates were then used to drive MAGFLOW simulations to chart the spread of lava as a function of time. Based on a classification on durations and lava volumes of ∼130 paroxysms at Etna in the past 13 years, and on lava flow path simulations of expected eruptions, we constructed a lava flow invasion hazard map for summit eruptions, providing a rapid response to the impending hazard. This allowed key at‐risk areas to be rapidly and appropriately identified.

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Since the mechanical properties of lava change over time, lava flows represent a challenge for physically based modeling. This change is ruled by a temperature field which needs to be modeled. MAGFLOW Cellular Automata (CA) model was developed for physically based simulations of lava flows in near real-time. We introduced an algorithm based on the Monte Carlo approach to solve the anisotropic problem. As transition rule of CA, a steadystate solution of Navier-Stokes equations was adopted in the case of isothermal laminar pressure-driven Bingham fluid. For the cooling mechanism, we consider only the radiative heat loss from the surface of the flow and the change of the temperature due to mixture of lavas between cells with different temperatures. The model was applied to reproduce a real lava flow that occurred during the 2004-2005 Etna eruption. The simulations were computed using three different empirical relationships between viscosity and temperature.

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