When this highly explosive volcano reactivates again, the methods presented here can be used as a framework to analyze monitoring data and facilitate the implementation of timely mitigation actions. Furthermore, this method graphically depicts the evolution of the indicators, easing the communication with non-specialist during volcanic crises. Our results show that this method is useful to identify indicators associated with different eruptive phases, recognize significant changes and underscore the lessons from this eruption. As a case study, we apply this method to the available data of the 1982 eruption of El Chichón volcano. For short-term assessment, we use a Bayesian method to examine the evolution of indicators derived from volcano monitoring. Moreover, we included additional nodes for the threatened zones and population according to the published hazards maps. For instance, the probability of at least one magmatic/hydromagmatic unrest episode (4.0%) producing an explosive eruption (75%) with VEI 4 (21.4%) in any 10-yt time interval is 0.64%. For long-term assessment, we present the event tree for this volcano including the probabilities of different scenarios based on its past activity. Here, we use a Bayesian inference approach to provide simple, objective and quantitative schemes for long- and short-term hazard assessment for El Chichón volcano. This eruption took by surprise authorities, population and scientists, thus preventing the implementation of timely and effective mitigation measures. The 1982 eruption of El Chichón volcano constitutes the worst volcanic disaster in Mexico producing more than 2000 fatalities, thousands of displaced people and severe economic losses. Ultimately, this may contribute to repeatedly revised risk areas on permanently active volcanoes, especially those that Recurrent UAV surveys enable the monitoring of temporal morphologic changes and aid the interpretation of observed changes in eruption style. To vent geometry and their strong control on the directionality of explosions. This period includes two paroxysmal explosions (3 July and 28 August 2019) and exhibited significant changes on day-to-month timescales. Here, we compare five high-resolution topographic data sets (<4 cm/pixel) of volcanicĬraters and vents from Stromboli volcano, Italy, that were acquired by unoccupied aerial vehicle (UAV) during five field campaigns between May 2019 and January 2020. In turn, the vent geometry strongly impacts the eruption characteristics. Gravitational instabilities and local accumulation of pyroclasts affect conditions at the active vents, through which gas-particle jets are released. These findings have implications for the distribution of volcanic ejecta and resulting areas at risk.Īctive volcanoes are typically subject to frequent substantial topographic changes as well as variable eruption intensity, The overpressure at the vent herby controls the direction of the asymmetry of the gas-particle jet. Our results reveal a strong influence of the vent geometry, on both the direction and the magnitude of particle spreading and the velocity of particles. Particle size and density as well as experimental pressure are varied. The “real” geometry is based on a photogrammetric 3D model of an active volcanic vent with a steep and a diverging vent side. The defining geometry elements of the “complex” vents are a bilateral symmetry with a slanted top plane. As volcanic vents can be expected to possess an irregular geometry, we utilise three vent designs, two “complex” vents and a vent with a “real” volcanic geometry. Here, we use scaled shock-tube experiments mimicking volcanic explosions in order to elucidate the effects of a number of initial conditions. Yet, it is not possible to observe directly the sub-surface parameters that drive such eruptions. The characteristics of this mixture in the near-vent region are a direct consequence of the underlying initial conditions at fragmentation and the geometry of the shallow plumbing system. Explosive volcanic eruptions eject a gas-particle mixture into the atmosphere.
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