Annals of Geophysics (INGV, Istituto Nazionale di Geofisica e Vulcanologia)
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Preface: Artificial Intelligence for Volcanology
No full textWhen a volcano erupts, it is essential to provide timely and accurate information on hazardous volcanic phenomena, their impacts, and the duration of the eruptive activity. However, volcanic eruptions are inherently complex processes governed by the interaction of multiple physical and chemical phenomena, often nonlinear and stochastic. The many uncertainties in key parameters make precise forecasting of eruptions in time and space particularly challenging – volcanic events can be intrinsically unpredictable. Despite these limitations, significant progress has been made in forecasting volcanic hazards, and in specific circumstances, in developing predictive models. These advances are closely tied to the growing availability of large volumes of data collected through enhanced monitoring systems, including Earth observation satellites, and to the rapid development of computational resources. This has encouraged the widespread adoption of data-driven approaches – particularly artificial intelligence (AI) techniques – to support decision-making in volcanology. AI technologies, which allow computers to learn from data, are increasingly used to monitor, analyze, and forecast volcanic activity. They support both real-time surveillance and retrospective hazard assessments through modeling tools. Looking ahead, combining AI with physical constraints represents a promising strategy to enhance the interpretability and reliability of predictions. Hybrid approaches – blending physics-based simulations, machine learning, and data fusion – are being actively developed to fully exploit computational power and improve flexibility in modeling complex volcanic dynamics
New developments in the estimation of tephra fallout hazard at Mt. Etna, in Italy, during the PANACEA project
Full text linkMount Etna, in Italy, is one the most active volcanoes in the world. Over the past two decades, its explosive activity has intensified, producing high eruptive columns that rise up to about 15 km above sea level. The particles ejected during these eruptions have caused numerous challenges for the population living on the volcano’s slope, mainly due to difficulties in removing the deposits, but also in terms of health risks and mobility disruptions. The increase in Etna’s explosive activity has led in continuous improvements in the monitoring and forecasting system adopted by the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, since 2009, using new sensors and enhanced data collection and analysis. In this paper, we present a review of several activities carried out in the frame of the Work Package 2 (WP2) of the ‘Probabilistic AssessmeNt of volCano-related multi-hazard and multi-risk at Mount EtnA (PANACEA)’ project. While the PANACEA project aims at using accurate physics-based models and advanced probabilistic approaches to assess volcanic multi-hazards and identify at-risk zones, the WP2 objective is to improve previous studies on the tephra fallout hazards for Etna. In this context, various activities have been conducted such as: enrich the data collection of eruption source parameters by analysing previous studies and developing new methods for their quantification; improve hazard estimates using multi-model approaches; quantify the uncertainty in eruption source parameters. Additionally, progresses have been made in developing hazard maps that include ballistic impact analysis. These approaches may be extended to other active volcanoes where advanced monitoring and surveillance systems are in place
Use of in situ tests to measure and predict shear wave velocity: the peculiarity of silty-sandy deposits in Emilia (Italy)
No full textThe results of Medusa SDMT (Seismic Dilatometer) and SCPTu (Seismic Piezocone) that were performed in 2023 at two different sites in the Emilia (Italy) plain are described in this paper. The focus is on the measurement of the shear wave velocity () and the predictive capability of existing (cone penetration test – CPT and flat dilatometer – DMT based) empirical correlations. Both the pseudo-interval and true interval approaches were applied when interpreting the in situ measurements. The comparison between measured (SDMT – true interval) and predicted from four different CPT and one DMT empirical correlations shows that not all of them have good performance. In this respect, we propose an updated DMT correlation to improve the accuracy of the predicted in silty-sandy deposits, which are predominant in the sites investigated in this paper. The studies connected to these peculiar intermediate soils are still ongoing and their behavior needs further research sites to test and validate this preliminary correlation
A study on the effects of effusion rate on 2D numerical simulations of lava flow evolution
Full text linkThe effusion rate plays a crucial role in controlling the evolution of volcanic eruptions and it is thus critical to quantify the associated volcanic hazards. It represents the volume of lava emitted over time and can be estimated using satellite remote sensing data, such as Volcanic Radiative Power (VRP) measurements, deriving the Time Averaged Discharge Rate (TADR). Variations in the effusion rate can influence the resulting eruption style, ranging from effusive or Strombolian to lava fountaining activity. Thanks to the abundance of free data collected through fieldwork and remote sensing, it is now possible to numerically simulate eruptive behaviors with Computational Fluid Dynamics (CFD) models, allowing for a detailed study of lava flow evolution in time and space, without the dangers of collecting field data. We have already largely simulated lava flows with a Lagrangian mesh‑free particle CFD method, known as Smoothed Particle Hydrodynamics (SPH). This model takes in input the physical parameters of the fluid and returns in output a numerical simulation of its spatio‑temporal evolution. Here, we propose a framework to simulate lava flows with a range of values for some physical parameter, to better understand their results on numerical simulations, bringing to a deeper knowledge of the different eruptive behaviors in function of these parameters. In particular, we conduct a study on the effusion rate effects over 2D numerical simulations of lava using numerical physical‑mathematical models that return as output not only the evolution of the flow front but also the behavior of the vertical flow section. Using the TADR derived from VRP data and the SPH method, we simulate the fluid flow under different effusion rate conditions. This sensitivity analysis demonstrates how varying effusion rates affect the evolution of the flow front and vertical cross‑section. In detail, we show how time‑independent and time‑dependent effusion rates, obtained by satellite data, can make possible to qualitatively analyze and reproduce different eruptive styles, as effusive, Strombolian, or explosive activity and variable flows. The results highlight the potential for integrating real observations with numerical models and lay the groundwork for future applications that combine these approaches with artificial intelligence to enhance the model performance
Modeling two-ways fluid-solid phase transitions in lava using Smoothed Particle Hydrodynamics
Full text linkPhase transitions are a key phenomenon in the evolution of lava flows, significantly influencing their emplacement and the formation of geological features such as lava channels and lava tubes. Here, a numerical model employing Smoothed Particle Hydrodynamics (SPH) to simulate two-way phase transitions between solid and fluid states in lava is presented. By accurately representing the solidification dynamics and incorporating a temperature range that accounts for the solidus and liquidus temperatures, the model addresses limitations in previous approaches that relied on oversimplified phase transition assumptions. We validate the model against Stefan’s benchmark test case and apply it to two illustrative volcanic scenarios using artificial volcanic-like environments,demonstrating how the model effectively captures the processes of solidification and fusion within the modeled lava flow. The results underscore the importance of phase transition modeling in understanding the complex behavior of lava flows in real-world volcanic contexts
Joint Norwegian and Croatian temporary seismic stations deployment within AdriaArray – the CRONOS network
Full text linkThis work presents an overview on the deployment of temporary seismic stations in the central part of the External Dinarides, aimed at enhancing our understanding of local seismic activity and tectonic processes. The deployment involved the installation of 12 new broadband stations over a period of two years. The seismometers were installed on solid building foundations lying directly on (or very close to) bedrock, providing an optimal tradeoff between ground coupling, instrument safety, and access to the power grid. Excluding one station that experienced early irreparable failure, the temporary network achieved a data recovery of the order of 87%. These temporary stations, in conjunction with several pre-existing permanent seismic instruments, allowed for the collection of high-resolution seismic data. This combined dataset was analyzed to identify seismic patterns and contribute to the broader knowledge of the Dinarides tectonic framework. The findings highlight the significance of temporary seismic networks in advancing earthquake monitoring and risk mitigation efforts in seismically active regions
Geophysical prospection for sustainable groundwater management: strategies for regional water resource optimization
Full text linkThis study employs an integrated geophysical approach, combining Electrical Resistivity Tomography (ERT) with Dipole-Dipole, Pole-Dipole, and Pole-Pole arrays and Vertical Electrical Sounding (VES) with a Schlumberger array, to delineate groundwater resources in the municipality of Sucupira do Norte, Maranhão, Brazil, a region with water scarcity. The survey successfully identified three aquiferunits: a shallow unconfined aquifer (<35 m depth; 10 to 100 Ω∙m) considered unsuitable for use due to the risk of contamination, and two deeper confined aquifers. Aquifer B was identified at depths of 60 to 90 m, with resistivity values of 500 to 600 Ω∙m, while the main target, Aquifer C, was found at depths of 140 to 190 m, with lower resistivity values of 50 to 100 Ω∙m, indicative of water-saturated sandstones within the Pedra de Fogo Formation. Based on these results, two specific drilling locations were defined, with recommended depths of 160 m and 270 m to ensure sustainable production. The results demonstrate the effectiveness of integrating Electrical Resistivity Tomography (ERT) and Vertical Electrical Sounding (VES) to reduce uncertainty in exploration and provide a robuststrategy for the sustainable management of groundwater in drought-prone regions
The seismic network in the Carpathian region of Ukraine
Full text linkThe Carpathian region of Ukraine plays a critical role in seismic monitoring due to its tectonic setting and proximity to the Vrancea Seismic Zone, which is known for its deep‑focus earthquakes. The regional seismic network across western Ukraine, covering the Carpathian and adjacent areas, currently comprises 22 stations, of which 5 are not operational, 18 stations continue to operatewith Soviet‑era long‑ or short‑period sensors. Data from these stations are archived locally and are not publicly accessible. Five stations in the Carpathians (UT.BRIU, UT.KSV, UT.MEZ, UT.RAKU, UT.STNU) were recently upgraded with modern broadband sensors (deployed alongside the existing instruments) under the ORFEUS Data Integration Grant. This grant, funded through the Geo‑INQUIRE Project and supported by in‑kind contributions from GFZ Helmholtz Centre for Geosciences, GaiaCode, and CNRS Geoazur, provided instruments and technical support that strengthened the network and enabled the station upgrades between September 2024 and March 2025. Data from the upgraded stations are available in real time through the European Integrated Data Archive (EIDA) under the FDSN network code UT, Ukrainian National Seismic Network, and can be accessed via the National Institute for Earth Physics (NIEP) EIDA node in Romania. For the first time, data from Subbotin Institute of Geophysics seismic network have been integrated into EIDA, significantly improving data accessibility and fostering international collaboration. These stations also contribute to the AdriaArray initiative, providing a dense seismic network for monitoring the Adriatic Plate and its active margins. This paper discusses the background, current state, and recent advancements in the region’s seismic network, with a focus on the upgrade of selected stations
Assessing Station Performance in the Adria Array: A Study of CSS Deployments
Full text linkThe Croatian Seismological Survey (CSS) plays a central role in seismic monitoring throughout Croatia with its permanent, temporary and mobile station networks. As part of the AdriaArray initiative, the CSS has expanded its capabilities by integrating its stations into a regional framework aimed at improving seismic coverage. In this study, the performance of three representative stations MOSL (permanent), 7433 (temporary) and BATN (mobile) is evaluated by analyzing the probabilistic power spectral density (PPSD). Results indicate that the permanent station exhibits superior performance, with noise levels better aligned with the New Low Noise Model (NLNM), whereas temporary and mobile stations show significantly higher noise at periods of 0.07‑1 s.
However, signal quality is affected by significant issues such as insufficient thermal and barometric insulation and shallow installations. While temporary and mobile stations show lesser performance overall, in range of 1‑10 s they are comparable to permanent stations in some aspects. Further, they exhibit higher noise levels at periods of 10‑100 s, which is influenced by environmental and anthropogenic factors. Improving seismic network performance in Croatia requires upgrading equipment, implementing deeper vault designs, and optimizing station locations to minimize noise interference. These results provide important insights for the modernization of seismic monitoring in Croatia and its integration into international initiatives
Methods for data and metadata quality tests of large dense seismic networks – focus on AdriaArray
Full text linkData quality checks are essential for any broad‑band seismological network, and in particular for data of temporary passive seismic experiments. These data quality checks concern (i) the availability and retrievability of the data from public data archives, (ii) the noise conditions at the stations, (iii) formal properties and the correctness of metadata, (iv) the mutual consistency between data and metadata, and finally (v) the quality of the data itself. Methods for these checks are introduced and applied to the AdriaArray Seismic Network. We present techniques for evaluating the quality of individual stations as well as techniques that allow us to detect outlying amplitudes and arrival times in case of a dense network. Results of the tests are summarized in the form of maps and in addition, details are given in an online repository. Our checks are continuously repeated and results are updated to secure high data quality. The aim of our study is to provide the user with useful information on the quality of AdriaArray data, as well as with suggestions for their own data quality assessment. In addition, the presented data quality checks form the basis for data curation by station and network operators. The suggested approaches can also be applied to other large dense seismic networks