Finite element modeling of ground deformation and gravity field at Mt. Etna

An elastic 3-D axi-symmetric model based on Finite Element Method (FEM) is proposed to compute ground deformation and gravity changes caused by overpressure sources in volcanic areas. The numerical computations are focused on the modeling of a complex description of Mt Etna in order to evaluate the effect of topography, medium heterogeneities and source geometries. Both ground deformation and gravity changes are investigated by solving a coupled numerical problem considering a simplified ground surface profile and a multi-layered crustal structure inferred from seismic tomography. The role of the source geometry is also explored taking into account spherical and ellipsoidal volumetric sources. The comparison between numerical results and those predicted by analytical solutions disclosed significant discrepancies. These differences constrain the applicability of simple spherical source and homogeneous half-space hypotheses, which are usually implicitly assumed when analytical solutions are applied

New data from borehole strainmeters to infer lava fountain sources (Etna 2011-2012)

In January 2011 eruptive activity resumed at Etna producing a new phase with frequent lava fountain episodes until April 2012. In November 2011, the first two borehole strainmeters were installed, which detected negative strain changes (~ 0.15 - 0.8 strain) during the paroxysmal events. A Finite Element Model was set up to estimate accurately the tilt and volumetric strain, taking into account the real profile of the volcano and the elastic medium heterogeneity. The numerical computations indicated an elongated depressurizing source located at 0 km b.s.l., which underwent a volume change of ~2 x 106 m3 which is the most of the magma volume erupted while a smaller remaining part is accommodated by the magma compressibility. This shallow source cannot accumulate large magma volumes and, thus, favours short term periodic eruptive events with a fairly constant balance between the refilling and the erupted magma

Integrated inversion of ground deformation and magnetic data at Etna volcano using a genetic algorithm technique

Geodetic and magnetic investigations have been playing an increasingly important role in studies on Mt. Etna eruptive processes. During ascent, magma interacts with surrounding rocks and fluids, and inevitably crustal deformation and disturbances in the local magnetic field are produced. These effects are generally interpreted separately from each other and consistency of interpretations obtained from different methods is qualitatively checked only a posteriori. In order to make the estimation of source parameters more robust we propose an integrated inversion from deformation and magnetic data that leads to the best possible understanding of the underlying geophysical process. The inversion problem was formulated following a global optimization approach based on the use of genetic algorithms. The proposed modeling inversion technique was applied on field data sets recorded during the onset of the 2002-2003 Etna flank eruption. The deformation pattern and the magnetic anomalies were consistent with a piezomagnetic effect caused by a dyke intrusion propagating along the NE direction

Multifractality in local geomagnetic field at Etna volcano, Sicily (southern Italy)

International audienceWe applied the Multifractal Detrended Fluctuation Analysis (MF-DFA), which allows to detect multifractality in nonstationary signals, to the hourly means of local geomagnetic field recorded at Mt. Etna volcano (southern Italy). We studied the signal measured at one geomagnetic station, installed at the summit of volcano, which was characterized by a strong eruption on 27 October 2002. We analyzed two frames of signals, one measured before the eruption and the other after, in order to evaluate dynamical changes induced by the eruptive event. Our findings show that: i) the geomagnetic time series is multifractal; ii) the multifractal degree of the signal decreases after the occurrence of eruption. This study aims to propose another approach to investigate the complex dynamics of volcano-related geomagnetic field

fem and ann combined approach for predicting pressure source parameters at etna volcano

Abstract. A hybrid approach for forward and inverse geophysical modeling, based on Artificial Neural Networks (ANN) and Finite Element Method (FEM), is proposed in order to properly identify the parameters of volcanic pressure sources from geophysical observations at ground surface. The neural network is trained and tested with a set of patterns obtained by the solutions of numerical models based on FEM. The geophysical changes caused by magmatic pressure sources were computed developing a 3-D FEM model with the aim to include the effects of topography and medium heterogeneities at Etna volcano. ANNs are used to interpolate the complex non linear relation between geophysical observations and source parameters both for forward and inverse modeling. The results show that the combination of neural networks and FEM is a powerful tool for a straightforward and accurate estimation of source parameters in volcanic regions

Inverse modeling in geophysical applications

The interpretation of the potential ¯eld data is an useful tool that allows for both investigating the subsurface structures and providing a quantitative evalu- ation of the geophysical process preceding and accompanying period of volcanic unrest. Potential ¯eld inversion problem are required to combine forward mod- els with appropriate optimization algorithms and automatically ¯nd the best set of parameters that well matches the available observations. Indeed, investi- gations on the mathematical equations to be inverted, have revealed that these models are ill-posed and highly non-linear. Numerical methods for modeling potential ¯eld observations are proposed and applied on real dataset

Non-linear analysis of geomagnetic time series from Etna volcano

An intensive nonlinear analysis of geomagnetic time series from the magnetic network on Etna volcano was carried out to investigate the dynamical behavior of magnetic anomalies in volcanic areas. The short-term predictability of the geomagnetic time series was evaluated to establish a possible low-dimensional deterministic dynamics. We estimated the predictive ability of both a nonlinear forecasting technique and a global autoregressive model by comparing the prediction errors. Our findings highlight that volcanomagnetic signals are the result of complex processes that cannot easily be predicted. There is slight evidence based on nonlinear predictions, that the geomagnetic time series are to be governed by many variables, whose time evolution could be better regarded as arising from complex high dimensional processes

FEM and ANN combined approach for predicting pressure source

A hybrid approach for forward and inverse geophysical modeling, based on Artificial Neural Networks (ANN) and Finite Element Method (FEM), is proposed in order to properly identify the parameters of volcanic pressure sources from geophysical observations at ground surface. The neural network is trained and tested with a set of patterns obtained by the solutions of numerical models based on FEM. The geophysical changes caused by magmatic pressure sources were computed developing a 3-D FEM model with the aim to include the effects of topography and medium heterogeneities at Etna volcano. ANNs are used to interpolate the complex non linear relation between geophysical observations and source parameters both for forward and inverse modeling. The results show that the combination of neural networks and FEM is a powerful tool for a straightforward and accurate estimation of source parameters in volcanic regions

Volcanomagnetic Evidence of the Magmatic Intrusion on 13th May 2008

During the onset of 2008 volcanic crisis at Mt Etna, the near-real time magnetic data provided a continuous updating of the volcano activity state on the northern flank. On the morning of 13th May 2008, significant local magnetic field changes marked the resumption of the eruptive activity characterized by the opening of a fracture field on the northern flank, and an eruptive fissure in the Valle del Bove. In agreement with the northward propagation of seismic events, magnetic signals at 5 stations in the summit area revealed a nearly NNW-SSE oriented magmatic intrusion, which started at about 9:00 GMT, propagated northward for about 2 km, and stopped at 14:00 GMT before reaching the North-East Rift. Magnetic variations, with amplitude ranging between 1.8 nT and -6.5 nT, are consistent with those calculated from piezomagnetic models, where stress-induced changes in rock magnetization are produced by the magmatic intrusion

Modeling of ALOS and COSMO-SkyMed satellite data at Mt Etna: implications on relation between seismic activation of the Pernicana fault system and volcanic unrest

We investigate the displacement induced by the 2–3 April 2010 seismic swarm (the largest event being of Ml 4.3 magnitude) by means of DInSAR data acquired over the volcano by the Cosmo-SkyMed and ALOS radar systems. Satellite observations, combined with leveling data, allowed us to perform a high-resolution modeling inversion capable of fully capturing the deformation pattern and identifying the mechanism responsible for the PFS seismic activation. The inversion results well explain high gradients in the radar line of sight displacements observed along the fault rupture. The slip distribution model indicates that the fault was characterized by a prevailing left-lateral and normal dip–slip motion with no fault dilation and, hence, excludes that the April 2010 seismic swarm is a response to accommodate the stress change induced by magma intrusions, but it is due to the tectonic loading possibly associated with sliding of the eastern flank of the volcano edifice. These results provide a completely different scenario from that derived for the 22 September 2002 M3.7 earthquake along the PFS, where the co-seismic shear-rupture was accompanied by a tensile mechanism associated with a first attempt of magma intrusion that preceded the lateral eruption occurred here a month later. These two opposite cases provide hints into the behavior of the PFS between quiescence and unrest periods at Etna and pose different implications for eruptive activity prediction and volcano hazard assessment. The dense pattern of ground deformation provided by integration of data from short revisiting time satellite missions, together with refined modeling for fault slip distribution, can be exploited at different volcanic sites, where the activity is controlled by volcano-tectonic interaction processes, for a timely evaluation of the impending hazards