Privitera, Eugenio

Monitoring volcanic activity is a complex task, given the intricate nature of volcanic processes and the diverse eruptive styles exhibited by different volcanoes. Early Detection (ED) systems have emerged as indispensable tools for mitigating potential risks associated with volcanic eruptions. The effectiveness of these systems is contingent upon their ability to provide timely and accurate alerts, as false alarms or missed warnings can lead to economic repercussions and pose risks to infrastructure and human safety. Evaluating the reliability of the ED systems may be paramount not only for effective hazard mitigation but also for facilitating the implementation and optimization of an ED model. However, developing an ED model is a challenging and labor-intensive endeavor, also requiring a deep understanding of advanced techniques and a meticulous calibration of various parameters. In response to these challenges, we present the Framework for Evaluation of Early Detection Systems (FEEDS). FEEDS is a comprehensive Python-based package designed to automatically assess the generalization capability of generic ED systems through cross-validation. The framework introduces a generic class representing the ED model identified solely through data, enabling a systematic assessment based on essential predictive parameters, including True Positive Rate, False Discovery Rate, prediction time, and Fraction of Time in Alarm, by performing a simulation. To validate the effectiveness of FEEDS, we utilized tiltmeter and strainmeter data recorded at Stromboli volcano between 2007 and 2019. These datasets, managed by Istituto Nazionale di Geofisica e Vulcanologia and Università di Firenze, were employed to implement FEEDS with a customized model for the early detection of the paroxysmal activity affecting the volcano during the period of the study, demonstrating the practical applicability and reliability of this framework in real-world volcanic monitoring scenarios. FEEDS may represent a valuable contribution to the ongoing efforts to enhance ED systems and their application in mitigating volcanic hazards. The development of a robust framework that automates the standard evaluation process not only streamlines system implementation but also reduces user efforts and establishes a common ground for assessing the reliability and performance of different ED models, contributing significantly to the advancement of volcanic monitoring capabilities.

La Fossa Caldera at Vulcano (Italy) has been showing signs of unrest since September 2021. To investigate this phenomenon, we conducted an analysis of geodetic and seismological data from July to December 2021. In particular, we analyzed Multi Temporal Interferometric Synthetic Aperture Radar and Global Navigation Satellite System data, showing a pronounced elliptical uplift signal, which we elaborated using analytical source modeling. Additionally, seismic data were used to identify seismicity associated with hydrothermal system activity and assess its temporal evolution. The results indicate that the observed deformation is consistent with the expansion of the hydrothermal system within the La Fossa Caldera. These findings align with the analysis of seismic data, revealing signals indicative of hydrothermal activity, such as Very Long Period events. The results suggest that the ongoing phenomenon since 2021 represents a hydrothermal unrest, similar to the one observed during the late 1970s to early 1990s.

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 CO2 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.

Infrasound signals are used to investigate and monitor active volcanoes during eruptive and degassing activity. Infrasound amplitude information has been used to estimate eruptive parameters such as plume height, magma discharge rate, and lava fountain height. Active volcanoes are characterized by pronounced topography and, during eruptive activity, the topography can change rapidly, affecting the observed infrasound amplitudes. While the interaction of infrasonic signals with topography has been widely investigated over the past decade, there has been limited work on the impact of changing topography on the infrasonic amplitudes. In this work, the infrasonic signals accompanying 57 lava fountain paroxysms at Mt. Etna (Italy) during 2021 were analyzed. In particular, the temporal and spatial variations of the infrasound amplitudes were investigated. During 2021, significant changes in the topography around the most active crater (the South East Crater) took place and were reconstructed in detail using high resolution imagery from unoccupied aerial system surveys. Through analysis of the observed infrasound signals and numerical simulations of the acoustic wavefield, we demonstrate that the observed spatial and temporal variation in the infrasound signal amplitudes can largely be explained by the combined effects of changes in the location of the acoustic source and changes in the near-vent topography, together with source acoustic amplitude variations. This work demonstrates the importance of accurate source locations and high-resolution topographic information, particularly in the near-vent region where the topography is most likely to change rapidly and illustrates that changing topography should be considered when interpreting local infrasound observations over long time scales.

The eruption of the volcano Hunga Tonga-Hunga Ha‘apai on Jan 15, 2022, 04:14:54 UTC, was such energetic that instruments observed different physical phenomena all over the globe. In Italy, the Istituto Nazionale di Geofisica e Vulcanologia (INGV), who is continuously operating different kinds of monitoring networks, as e.g., the Italian Seismic Network (ISN), micro-barometric and infrasonic stations for monitoring the active volcanoes, ionospheric monitoring network (GNSS and ionosonde), recorded seismic, acoustic and electromagnetic signals originated by this exceptional event. The blast wave generated by the volcanic explosion of Hunga Tunga was recorded by the micro-barometric and infrasound stations installed at Phlegrean Fields (PF), at Stromboli volcano and on Mt. Etna. The first arrival was recorded at ~20:00 UTC, after travelling along the “short” great circle (17600 km), was succeeded by a second onset, about 3:40 h later, arriving at PF from the opposite direction. The mean propagation velocity in both directions was calculated as 310 m/s. The stations of the Etna Radio Observatory (ERO) are also equipped with micro-barometers, measuring the atmospheric pressure at a sampling rate of 5 min. The first group of atmospheric shock waves was recorded in the evening of Jan 15, 2022, while 36 hours later the ERO-stations observed a second signal after having completed the second orbit. The magnitude of M5.7 of the Hunga Tonga eruption was strong enough to record core phases (PKIKP, PKP), surface reflection of mantle phases (PP, SS), as well as Rayleigh and Love waves, at many stations of the ISN. The atmospheric waves generated by the eruption generated Travelling Ionospheric Disturbances in the ionosphere detected as disturbances in the Total Electron Content calculated by using GNSS data acquired by the GNSS network of INGV and variations of the ionospheric peak layer parameters (foF2, hmF2), recorded by the ionosonde installed on the Italian territory by INGV.

The gradual temporal shift of the spectral lines of harmonic seismic and/or acoustic tremor, known as spectral gliding, has been largely documented at different volcanoes worldwide. Despite the clear advantage of the experimental approach in providing direct observation of degassing processes and related elastic radiation, experimental studies on gliding tremor are lacking. Therefore, we investigated different episodes of gliding of acoustic and seismic tremor observed during analogue degassing experiments performed under different conditions of magma viscosity (10-1,000 Pa s), gas flux (5-180×10−3 l/s) and conduit surface roughness (fractal dimension of 2-2.99). Gliding experimental harmonic seismic and acoustic tremor was observed at high gas flux rates and viscosities, mostly associated with an increasing trend and often preceding a major burst. Decreasing secondary sets of harmonic spectral lines were observed in a few cases. Results suggest that gliding episodes are mostly related to the progressive volume variation of shallow interconnected gas pockets. Spectral analyses performed on acoustic signals provided the theoretical length of the resonator that was compared against the temporal evolution of the gas pockets, quantified from video analyses. The similarities between the observed degassing regime and churn-annular flow in high viscous fluids encourage further studies on churn dynamics in volcanic environments.

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.

In November 2019, the fourth meeting on Volcano Observatory Best Practices workshop was held in Mexico City as a series of talks, discussions, and panels. Volcanologists from around the world offered suggestions for ways to optimize volcano-observatory crisis operations. By crisis, we mean unrest that may or may not lead to eruption, the eruption itself, or its aftermath, all of which require analysis and communications by the observatory. During a crisis, the priority of the observatory should be to acquire, process, analyze, and interpret data in a timely manner. A primary goal is to communicate effectively with the authorities in charge of civil protection. Crisis operations should rely upon exhaustive planning in the years prior to any actual unrest or eruptions. Ideally, nearly everything that observatories do during a crisis should be envisioned, prepared, and practiced prior to the actual event. Pre-existing agreements and exercises with academic and government collaborators will minimize confusion about roles and responsibilities. In the situation where planning is unfinished, observatories should prioritize close ties and communications with the land and civil-defense authorities near the most threatening volcanoes.

The Istituto Nazionale di Geofisica e Vulcanologia (INGV) is an Italian research institution with focus on earth sciences. Moreover, the INGV is the operational center for seismic surveillance and earthquake monitoring in Italy and is a part of the civil protection system as a center of expertise on seismic, volcanic, and tsunami risks.INGV operates the Italian National Seismic Network and other networks at national scale and is a primary node of the European Integrated Data Archive for archiving and distributing strong‐motion and weak‐motion seismic recordings. In the control room in Rome, INGV staff performs seismic surveillance and tsunami warning services; in Catania and Naples, the control rooms are devoted to volcanic surveillance. Volcano monitoring includes locating earthquakes in the regions around the Sicilian (Etna, Eolian Islands, and Pantelleria) and the Campanian (Vesuvius, Campi Fregrei, and Ischia) active volcanoes. The tsunami warning is based on earthquake location and magnitude (M) evaluation for moderate to large events in the Mediterranean region and also around the world. The technologists of the institute tuned the data acquisition system to accomplish, in near real time, automatic earthquake detection, hypocenter and magnitude determination, and evaluation of several seismological products (e.g., moment tensors and ShakeMaps). Database archiving of all parametric results is closely linked to the existing procedures of the INGV seismic surveillance environment and surveillance procedures. Earthquake information is routinely revised by the analysts of the Italian seismic bulletin. INGV provides earthquake information to the Department of Civil Protection (Dipartimento di Protezione Civile) to the scientific community and to the public through the web and social media. We aim at illustrating different aspects of earthquake monitoring at INGV: (1) network operations; (2) organizational structure and the hardware and software used; and (3) communication, including recent developments and planned improvements.

Considering the peculiarities of the open conduit activity at Mount Etna, here we focused in the development of a dedicated event-tree-like conceptual model including all the potential activities that may occur at Mount Etna, including both central and lateral eruptions. This conceptual model represents the base for a further development of an exclusive dedicated probabilistic model, a study already ongoing in multiple Italian projects (e.g., AshResilience and IMPACT Projects).The general conceptual model presented here for the Etna eruptions, has been developed within the WP11 of the European project EUROVOLC.