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The interaction between volcanic activity and flank instability during the Christmas Eve eruption at Mount Etna in 2018 is explored, using a mechanically consistent inverse model fitting high spatial resolution SAR data. Inversions search for fractures that may be curved and can accommodate co‐eval pressure and shear stress changes. Displacements associated with the eruption result from the interaction between two intrusion sources: a buried dyke and a curved sheared intrusion that fed the eruption. Moreover, we identify that the sheared magmatic intrusion induced the observed eastward slip on the Pernicana fault, while the Fiandaca fault was undergoing stress accumulation, which was suddenly released during a M5.0 seismic event. The Fiandaca fault is determined to be listric, rooting beneath the mobile eastern flank of the volcano. This study highlights the role of curved fractures, acting as sheared intrusions or as faults, in volcanoes exhibiting flank instabilities. Plain Language Summary: In this study, we thoroughly examine how volcanic activity and flank dynamics interacted during the 2018 eruption of Mount Etna. We use high‐resolution satellite SAR data and a model considering complex mechanical aspects of the volcano's behavior. Formal inversions reveal that the eruption is triggered by the interplay between two intrusion sources: a buried dyke and a curved sheared intrusion, consistent with the earthquake pattern. This study emphasizes the significant role of curved sheared intrusions and faults at volcanoes prone to flank instabilities. Furthermore, we quantify how summit magmatic intrusions promote fault slip in the eastern flank of Etna. These findings differ from previous research that used simpler approaches. In summary, our study provides a new insight into how volcanoes like Etna can erupt and trigger flank slip, shedding light on the complex interactions between magma and tectonics. Key Points: Modeling shows that the magma intrusion feeding the 2018 eruption accommodated coeval opening and shear displacementsBoth the summit intrusions and the Fiandaca fault are curved, probably connected to the detachment at the base of the mobile eastern sectorThe Fiandaca fault was previously locked. It released accumulated stress, while the Pernicana fault passively responded to the intrusion [ABSTRACT FROM AUTHOR]

We have modeled the fast dike intrusion that started on 24 December 2018 at Mount Etna. The intrusion was accompanied by an intense seismicity swarm that also continued the following day. Since previous studies did not detail the overall chain of events in time during the magma ascent, here we propose a combined analytical and FEM modeling of all available continuous deformation data, focusing on the signals over 2 days (24–25 December) when the continuous deformation networks recorded clear variations directly related to the dike ascent. High‐rate GPS enabled obtaining an early and reliable source model. Borehole instruments (strainmeters and tiltmeters) highlighted clear variations, starting about 1 hr before those recorded by GPS, and moreover, made it possible to improve the dike ascent modeling. In particular, our continuous deformation data clearly revealed not one but two dikes and showed how they evolved in time. We inferred one dike that began propagating in the first kilometer above sea level, continued to rise with a maximum opening of 1.9 m and increased its horizontal dimension until reaching the ground surface. Soon after, continuous deformation networks revealed a new elongated intrusion in the southern flank, matching the south shifted position of the seismic swarm. This second dike, with a thicker opening of 4.9 m, started from a depth of about −3 km (below sea level) but did not reach the ground surface. This proposed multiparametric modeling of continuous deformation data has therefore enabled disentangling the complexity of the real volcanic processes. Key Points: Imaging multidisciplinary continuous deformation data to improve dike ascent modelingDetailed temporal model of the 2018 intrusion at Etna volcano [ABSTRACT FROM AUTHOR]

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Strainmeter and broadband seismic signals have been analyzed jointly with the aim of calibrating a borehole strainmeter at Etna volcano by using a seismo-geodetic technique. Our results reveal a good coherence between the dynamic strains estimated from seismometer data and strains recorded by a dilatometer in a low-frequency range [0.03-0.06 Hz] at the arrival of teleseismic waves. This significant coherence enabled estimating the calibration coefficient and making a comparison with calibration results derived from other methods. In particular, we verified that the proposed approach provides a calibration coefficient that matches the results obtained from the comparison of the recorded strain both with theoretical strain tides and with normal-mode synthetic straingrams. The approach presented here has the advantage of exploiting recorded seismic data, avoiding the use of computed strain from theoretical models. [ABSTRACT FROM AUTHOR]

Ground deformation and gravity changes in active calderas during periods of unrest can signal an impending eruption and thus must be correctly interpreted for hazard evaluation. It is critical to differentiate variation of geophysical observables related to volume and pressure changes induced by magma migration from shallow hydrothermal activity associated with hot fluids of magmatic origin rising from depth. In this paper we present a numerical model to evaluate the thermo-poroelastic response of the hydrothermal system in a caldera setting by simulating pore pressure and thermal expansion associated with deep injection of hot fluids (water and carbon dioxide). Hydrothermal fluid circulation is simulated using TOUGH2, a multicomponent multiphase simulator of fluid flows in porous media. Changes in pore pressure and temperature are then evaluated and fed into a thermo-poroelastic model (one-way coupling), which is based on a finite-difference numerical method designed for axi-symmetric problems in unbounded domains. Based on data for the Campi Flegrei caldera (Italy), a series of simulations assess the influence of fluid injection rates and mechanical properties on the hydrothermal system, uplift and gravity. Heterogeneities in hydrological and mechanical properties associated with the presence of ring faults are a key determinant of the fluid flow pattern and consequently the geophysical observables. Peaks (in absolute value) of uplift and gravity change profiles computed at the ground surface are located close to injection points (namely at the centre of the model and fault areas). Temporal evolution of the ground deformation indicates that the contribution of thermal effects to the total uplift is almost negligible with respect to the pore pressure contribution during the first years of the unrest, but increases in time and becomes dominant after a long period of the simulation. After a transient increase over the first years of unrest, gravity changes become negative and decrease monotonically towards a steady state value. Since the physics of the investigated hydrothermal system is similar to any fluid-filled reservoir, such as oil fields or CO2 reservoirs produced by sequestration, the generic formulation of the model will allow it to be employed in monitoring and interpretation of deformation and gravity data associated with other geophysical hazards that pose a risk to human activity. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We investigated time dependent piezomagnetic fields due to volcanic sources embedded in a viscoelastic, homogeneous half-space. Especially in volcanic areas, the presence of inhomogeneous materials and high temperatures produce a lower effective viscosity of the Earth's crust that calls for considering anelastic properties of the medium. Piezomagnetic properties are carried by grains of titano-magnetite, which occupy only a small fraction of ordinary rock volume and are supposed to be elastic, while the non-magnetic surrounding matrix is assumed to be viscoelastic. From all the possible rheological models, we investigated two cases in which the bulk modulus is purely elastic and the shear modulus relaxes as: (i) a Maxwell solid and (ii) a standard linear solid (SLS). We applied the Correspondence Principle to the analytical elastic solutions for pressurized spherical sources and dislocation sources in order to determine the time dependent piezomagnetic fields in a viscoelastic medium. The piezomagnetic field completely vanishes after the relaxation process for a Maxwell rheology, whereas it is found to decrease over time and reach some finite offset value for a SLS rheology. These different behaviours provide helpful hints in understanding the temporal evolution of piezomagnetic anomalies in volcanic regions. [ABSTRACT FROM AUTHOR]

We 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. [ABSTRACT FROM AUTHOR]

Distributed Dynamic Strain Sensing (DDSS), also known as Distributed Acoustic Sensing (DAS), is becoming a popular tool in array seismology. A new generation of engineered fibers is being developed to improve sensitivity and reduce the noise floor in comparison to standard fibers, which are conventionally used in telecommunication networks. Nevertheless, standard fibers already have extensive coverage around the Earth's surface, so it motivates the use of the existing infrastructure in DDSS surveys to avoid costs and logistics. In this study, we compare DDSS data from stack instances of standard multi-fiber cable with DDSS data from a co-located single-fiber engineered cable. Both cables were buried in an area located 2.5 km NE from the craters of Mt. Etna. We analyze how stacking can improve signal quality. Our findings indicate that the stack of DDSS records from five standard fiber instances, each 1.5 km long, can reduce optical noise of up to 20%. We also present an algorithm to correct artifacts in the time series that stem from dynamic range saturation. Although stacking is able to reduce optical noise, it is not sufficient for restoring the strain-rate amplitude from saturated signals in standard fiber DDSS. Nevertheless, the algorithm can restore the strain-rate amplitude from saturated DDSS signals of the engineered fiber, allowing us to exceed the dynamic range of the record. We present measurement strategies to increase the dynamic range and avoid saturation.

Volcano-seismic signals can help for volcanic hazard estimation and eruption forecasting. However, the underlying mechanism for their low frequency components is still a matter of debate. Here, we show signatures of dynamic strain records from Distributed Acoustic Sensing in the low frequencies of volcanic signals at Vulcano Island, Italy. Signs of unrest have been observed since September 2021, with CO 2 degassing and occurrence of long period and very long period events. We interrogated a fiber-optic telecommunication cable on-shore and off-shore linking Vulcano Island to Sicily. We explore various approaches to automatically detect seismo-volcanic events both adapting conventional algorithms and using machine learning techniques. During one month of acquisition, we found 1488 events with a great variety of waveforms composed of two main frequency bands (from 0.1 to 0.2 Hz and from 3 to 5 Hz) with various relative amplitudes. On the basis of spectral signature and family classification, we propose a model in which gas accumulates in the hydrothermal system and is released through a series of resonating fractures until the surface. Our findings demonstrate that fiber optic telecom cables in association with cutting-edge machine learning algorithms contribute to a better understanding and monitoring of volcanic hydrothermal systems., (© 2023. The Author(s).)

Understanding physical processes prior to and during volcanic eruptions has improved significantly in recent years. However, uncertainties about subsurface structures distorting observed signals and undetected processes within the volcano prevent volcanologists to infer subtle triggering mechanisms of volcanic phenomena. Here, we demonstrate that distributed acoustic sensing (DAS) with optical fibres allows us to identify volcanic events remotely and image hidden near-surface volcanic structural features. We detect and characterize strain signals associated with explosions and locate their origin using a 2D-template matching between picked and theoretical wave arrival times. We find evidence for non-linear grain interactions in a scoria layer of spatially variable thickness. We demonstrate that wavefield separation allows us to incrementally investigate the ground response to various excitation mechanisms. We identify very small volcanic events, which we relate to fluid migration and degassing. Those results provide the basis for improved volcano monitoring and hazard assessment using DAS., (© 2022. The Author(s).)

Unprecedented ultra-small strain changes (~10 -8 -10 -9 ), preceding and accompanying the 2017 explosive-effusive activity, were revealed by a high precision borehole strainmeter at Etna. No pre- or co-eruptive deformation was detected by the GPS measurements, which often fail to detect ground deformation engendered by short-term small volcanic events due to their limited accuracy (millimetres to few centimetres). Through the analysis and detection of ultra-small strain changes (few tens of nanostrain), revealed by filtering the raw data, a significant time correspondence with the eruptive activity is observed. For the first time, cyclic fast exponential strain changes, preceding the onset of eruptive events, with a timescale of about 2-7 days, were detected. These variations are attributable to the expansion of the shallow magma reservoir, which is replenished with new magma from depth during the inter-eruptive periods. Interpreting the strain changes in terms of pressurization/depressurization of the chamber due to the cyclic influx and withdrawal of magma, allows placing some constraints on the magma recharge volume rate. A Finite Element model has been developed to simulate the temporal evolution of the strain changes generated by the re-pressurization of a spheroidal magma source using a dynamical approach. An average total mass budget of about 1-2 × 10 9  kg, which is in the range of the erupted mass, is estimated to be accumulated within a shallow vertically elongated magma chamber during the inter-eruptive periods. Such evidence demonstrates that the near-real time analysis of strainmeter records is remarkable for its ability to record small transients and highlight recharging phases preceding eruptive activity, which would go undetected with other current methodologies. Under these conditions, the ability to simulate inter-eruptive periods offers an opportunity to estimate the magma recharge rate with important implications for volcano hazard assessment.

In Earth Sciences there is a growing interest in studies concerning soil-radon activity, due to its potential as a tracer of numerous natural phenomena. Our work marks an advance in the comprehension of the interplay between tectonic activity, volcanic eruptions and gas release through faults. Soil-radon measurements, acquired on Mt. Etna volcano in 2009-2011, were analyzed. Our radon probe is sensitive to changes in both volcanic and seismic activity. Radon data were reviewed in light of the meteorological parameters. Soil samples were analyzed to characterize their uranium content. All data have been summarized in a physical model which identifies the radon sources, highlights the mechanism of radon transport and envisages how such a mechanism may change as a consequence of seismicity and volcanic events. In the NE of Etna, radon is released mainly from a depth of <1400 m, with an ascent speed of >50 m/day. Three periods of anomalous gas release were found (February 2010, January and February 2011). The trigger of the first anomaly was tectonic, while the second and third had a volcanic origin. These results mark a significant step towards a better understanding of the endogenous mechanisms that cause changes in soil-radon emission at active volcanoes.

Long-term and high temporal resolution gravity and deformation data move us toward a better understanding of the behavior of Mt Etna during the June 1995 - December 2011 period in which the volcano exhibited magma charging phases, flank eruptions and summit crater activity. Monthly repeated gravity measurements were coupled with deformation time series using the Differential Synthetic Aperture Radar Interferometry (DInSAR) technique on two sequences of interferograms from ERS/ENVISAT and COSMO-SkyMed satellites. Combining spatiotemporal gravity and DInSAR observations provides the signature of three underlying processes at Etna: (i) magma accumulation in intermediate storage zones, (ii) magmatic intrusions at shallow depth in the South Rift area, and (iii) the seaward sliding of the volcano's eastern flank. Here we demonstrate the strength of the complementary gravity and DInSAR analysis in discerning among different processes and, thus, in detecting deep magma uprising in months to years before the onset of a new Etna eruption.