MagmaPropagator: A forecasting tool for location and time of volcanic eruptions due to off-conduit magma propagation.

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This project aims at developing a physics-based tool to forecast scenarios for the location and time of a fissure eruption following magma propagation below the surface. Often magma avoids the central conduit and propagates through tortuous pathways, eventually opening a new fissure on the volcano flanks or within a caldera. Such eruptive fissures are found in many areas now densely populated. The related hazard has sofar been estimated purely based on the spatial distribution of previous events.In the proposed research, we will take advantage of the knowledge accumulated in decades of magma propagation research, that is now mature enough for the creation of a forecasting tool based on mechanical principles. We will taylor our approach on three well-monitored cases: Campi Flegrei (Italy) is extremely high-risk and motivates development of near-real time forecasting methods; Etna, Italy, and Piton de la Fournaise, La Reunion have had frequent fissure eruptions and offer data-rich environment to test our models. Established deterministic models will be combined in order to retrieve simultaneously trajectory and timing information. We will use a Monte Carlo approach to invert for the current mechanical state of the volcano based on past eruptive patterns and data assimilation techniques to update forecasts based on data recorded during magma propagation. Synthetic data from analog laboratory experiments and numerical scenario simulations will be added to the data pool allowing us flexible testing and application to Campi Flegrei.The outcomes of this project will be: 1) A better understanding of how the state of stress of volcanoes of different shapes evolve with time and how the edifice history controls the migration of surface volcanism, 2) A long-term forecasting tool for the future distribution of eruptive vents, useful for land planning, 3) A short-term tool to update the forecast scenarios according to intrusion parameters progressively determined by assimilating monitoring data.