Annals of Geophysics (INGV, Istituto Nazionale di Geofisica e Vulcanologia)
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Research on Conventional ERT Inversion and Improved AMT Inversion Based on Deep Learning Denoising Data in Tunnel and Road Detection: A Case Study in Sichuan Province
Full text linkThe safety of tunnels and roads is crucial for traffic safety. Due to the presence of adverse geological features, which can cause serious problems in tunnels and on roads, there is an urgent need for comprehensive geophysical investigations to determine their distribution. This will provide additional technical information to help ensure the safety of engineering projects. This study uses the tunnels and roads in Jiulong County, Sichuan Province, as an example. Integrated geophysical methods were employed to arrange ERT sections at tunnel entrances and exits, as well as on geophysical slopes. The primary focus was on the thickness of the overlying layers and the geological conditions of the rock and soil within a certain depth range above the tunnel design line. For the longitudinal cross-section of the main tunnel, Audio Magnetotelluric (AMT) were primarily used to investigate fault zones, karst formations, aquifers and rock mass grades. Combining electromagnetic data denoising and inversion using a U-Net neural network with ERT inversion clearly revealed the underground geological conditions of the tunnel. The tunnel alignment is characterised by a mixture of stable quartz-rich rock masses and metamorphic rock masses. Overall, the deep rock mass of the tunnel axis is stable, with fractures in some transverse sections. The intersection is relatively stable, interspersed with weathered and fractured zones. These findings provide valuable insights into advancing geophysical techniques for investigating tunnel sites under complex geological conditions
Integrating the FXLand network into the real‑time earthquake surveillance and monitoring system of Italy
Full text linkThe Ionian margin of southern Italy is one of the most complex geodynamic regions in the central Mediterranean, where ongoing convergence between the African and Eurasian plates results in intense seismic activity and highly heterogeneous crustal structures. To improve seismic monitoring in this region, within the framework of the ERC Advanced Grant FOCUS (2018‑2025), a temporary onshore seismic network (FXLand) was deployed along the Ionian coasts of Sicily and Calabria from December 2021 to June 2023, complementing a marine array of ocean‑bottom seismometers operating during the same period. In this study we describe the deployment and performance of the 13 temporary broadband stations of FXLand. The network was integrated in real time into the Italian national seismic surveillance system, enhancing data availability and coastal network geometry. During the deployment, FXLand recorded, more than 1,500 local earthquakes and more than 200 teleseismic events with magnitude M ≥ 6. We also present results from the analysis of three seismic sequences that occurred during the network operational period. The application of a Template Matching technique to the combined permanent station and FXLand network dataset, we significantly increased the number of detected low‑magnitude earthquakes in onshore area, improving catalog completeness compared to real‑time surveillance and Italian Seismic Bulletin. On the other hand, the offshore sequence highlights the main limitations of land‑based networks in detecting and accurately locating submarine seismicity. The integration of marine observations from the ocean‑bottom seismometer network in the Ionian Sea is expected to provide substantial improvements in the detection and location accuracy of offshore earthquakes, contributing to a more complete characterization of seismic activity along the Ionian margin
Project Severe Weather Archive of the Philippines (SWAP). Part 2: Baseline Climatology of Close Proximity Soundings in Hailstorm Environments across Luzon, Philippines
No full textThe environments of severe thunderstorms that produced hail were examined using 171 proximity soundings (2005-2024) archived in the 3rd Data Release of Project SWAP. These soundings were categorized based on their geographical occurrence into three hail-prone environments across Luzon, Philippines. For each case, key parameters describing instability, vertical wind shear, and moisture were calculated to assess the environmental conditions for hail production. The probability of hail occurrence, expressed as a function of WMAX (√2 × CAPE) and 0-6 km bulk shear (DLS), revealed patterns distinct from those reported in other regions. Hail events in Luzon were most likely under high CAPE conditions, where boundary-layer moisture was sufficient, mid- and low-level lapse rates were steep, and lifting condensation levels were high. Surprisingly, weak DLS was common across Luzon hail environments, diverging from existing severe weather climatologies, yet large DCAPE indicated environments conducive to damaging wind events. When DLS was replaced with the shear magnitude between the cloud base and equilibrium level, the probability of hail occurrence increased, better aligning with global severe weather climatologies. This finding is supported by hodograph analyses, which show largely unidirectional wind profiles: strong speed shear aloft but weak directional shear in the low-levels. Parameters such as WMAXSHEAR, WMAXSHEARLCL-EL, and BWDLCL-EL emerge as potential discriminators between non-severe and severe thunderstorms capable of producing hail, and as useful metrics for assessing convective storm severity in Luzon and possibly countrywide. Finally, two recurring severe setups conducive to hail were identified: (1) an easterly regime associated with trade winds, and (2) a westerly regime linked to the Asian summer monsoon
Encoding Gridded Atmospheric Data with Classical and Quantum Methods
No full textAccurate encoding of spatial meteorological data is critical for applying quantum machine learning (QML) in climatology and atmospheric sciences—important domains for geospatial methods. This study explores quantum encoding techniques adapted to the constraints of limited qubit space, focusing on gridded numerical weather prediction (NWP) outputs related to low-visibility events at multiple Czech airports. Beyond quantum encoding, we investigate the role of dimensionality reduction (PCA, t-SNE, UMAP, Isomap) and its integration with quantum amplitude and angle encoding schemes. We assess their capacity to represent visibility transitions using fidelity-based measures. Results indicate spatial heterogeneity in encoding effectiveness, with no single method dominating across all locations. To better preserve spatial and physical structure, we introduce expert-informed groupwise embeddings applied separately on meteorological clusters, rather than across the entire dataset. This approach improves the physical relevance and continuity of spatial patterns. Results suggest that temporal features (diurnal cycles), complicate fidelity assessment and emphasize the importance of temporal segmentation and data curation. Our findings demonstrate that combining classical dimensionality reduction, quantum encoding, and domain expertise offers a promising path toward effectively representing complex spatial-temporal atmospheric patterns. This work supports future development of quantum-assisted weather forecasting systems
Simulations of Complex Visco-Thermal Fluids with an AI-based CFD Emulator
Full text linkPhysical phenomena evolve in space and time following governing laws with a high level of complexity and mathematical models can help to make accurate predictions of their behavior, describing complex fluids with a good balance between accuracy and computational costs. We have long used detailed Computational Fluid Dynamics (CFD) models to simulate complex dynamics with high accuracy, but these simulations typically entail high computational costs, resulting in long execution times and the use of expensive computational resources. To overcome these limitations, we have recently integrated CFD with Artificial Intelligence (AI), in the so-called Emulators, to expand the scope of fluid modeling, improving its performance. Here, we present an AI-based CFD emulator for Smoothed Particle Hydrodynamics (SPH) simulations, which uses an Artificial Neural Network (ANN) to enhance simulations of complex fluids with viscous and thermal components.
We show the model capability to reproduce the spatio-temporal evolution of natural visco-thermal fluids. In addition, we demonstrate the emulator capacity to generalize its applicability to problems not encountered during the training phase. We also conduct a detailed error evaluation, showing that the minimal observed discrepancies do not compromise model accuracy and robustness, especially given the theoretical and computational advantages. These key points open this emulator to practical applications for natural fluids, e.g., oil, honey, or geophysical fluids such as lava, enhancing fluidmodeling performance and extending functionalities. The innovation of this method improves studies in the field of numerical simulations, for example in its use as a digital Twin of a physical phenomenon, for the study of the dynamics of the system without the need of large costs for field analysis or laboratory experiments.
Insights into the Salse di Regnano mud volcanoes: integrating geomagnetism, UAV photogrammetry and historical data
Full text linkThis study tries to advance the understanding of the Salse di Regnano mud volcanoes within the framework of an INGV project by integrating geomorphological, geochemical, historical, and remote-sensing data. Detailed analyses of morphology and geochemistry revealed distinctive geometric features and enabled reconstruction of the historical configuration of the area. The research was then extended by integrating drone-based geomagnetic surveys with digitized historical maps transformed into normalized 3D models. High-resolution topography derived from Structure-from-Motion (SfM) photogrammetry, complemented by satellite imagery and archival sources, allowed a comprehensive analysis of surface and subsurface patterns.
The resulting geomagnetic anomaly maps reveal a “tongue” of low values descending from the northern upper slope into the main mud area, which broadly aligns with relative morphological features. Additional anomalies highlight structures of potential geophysical interest for further investigation. Historical reconstruction indicates a markedly different summit in the early 20th century, dominated by a prominent emission cone that reshaped the area following a paroxysmal event in the 1930s.
Building upon previous findings, these new observations continue to provide guidance for subsequent investigations, which will include a targeted geophysical campaign combining passive seismic and electrical resistivity surveys to probe the subsurface. This multidisciplinary approach demonstrates the potential of integrating modern geophysical measurements with historical and morphological information, providing an evolving framework that adapts as new data become available and enhancing our understanding of the evolution of mud volcano systems over time
Discriminating the origin of obsidian fragments in archaeological contexts based on morphological features and geochemical data: the Breccia Museo (Campanian Ignimbrite eruption, Italy) case study
Full text linkA recent archaeological discovery on Vivara, the small islet next to Procida (Campania region, Italy), has documented the prehistoric use of finely crushed obsidian fragments as abrasive powder for polishing wooden artifacts. These fragments originated from a local deposit known as Breccia Museo – whose exploitation in prehistoric times had not been previously attested – and were found mixed with obsidian tools sourced from other well‑known Italian deposits widely used throughout prehistory. To develop effective methods for discriminating obsidian provenance, as required in this case, we carried out geochemical, isotopic, and mineralogical analyses on obsidian samples collected from the Breccia Museo outcrop at Punta della Lingua (~4 km NE of Vivara), one of the richest and most accessible deposit on Procida Island. The results were compared with those obtained from Breccia Museo obsidians from other local (Campi Flegrei) outcrops, as well as with reference samples from the major obsidian sources exploited in the Central‑Western Mediterranean during prehistory (Monte Arci, Palmarola, Lipari, and Pantelleria). In addition, a micromorphological and microanalytical study was performed to identify further distinctive features useful for recognizing Breccia Museo obsidian across different archaeological contexts. This interdisciplinary investigation highlights the potential of combining relatively rapid major/minor element analyses, mineralogical and morphological characterization, with more time‑consuming but highly precise isotopic measurements (87Sr/86Sr, 143Nd/144Nd) to achieve robust provenance discrimination
Investigating Stress Transfer and Fault Interaction in the July‑August 2025 Poso and Tokararu Earthquakes, Central Sulawesi, Indonesia
No full textThe July‑August 2025 earthquake in Central Sulawesi, which consisted of the Mw 5.9 Poso strike‑slip event and the Mw 6.0 Tokararu thrust event, offers new insights into stress transfer and fault interaction in a tectonically complex setting. We combined Coulomb stress modeling, HypoDD aftershock relocation, and ascending‑track DInSAR analysis to investigate the sequence. Relocation of 669 events sharpened fault geometries, with aftershocks of the Poso earthquake clustering along the Poso‑West segment and those of Tokararu aligning on a shallow thrust plane. Coulomb stress modeling shows that aftershocks correlate well with positive ΔCFS lobes for both events, supporting static stress transfer as a key mechanism, though no significant positive stress was transferred from Poso to Tokararu. DInSAR results reveal both pre‑ and co‑seismic deformation, with uplift reaching +16 cm and subsidence –13 cm at Poso, and uplift up to +13 cm and subsidence –14 cm at Tokararu. These signals suggest strain accumulation and possible aseismic slip preceding rupture. Geological contrasts within the Pompangeo Complex, where weak alluvial sediments overlie stronger metamorphic basement rocks, further explain the differences in rupture style. Together, these multidisciplinary findings highlight the interplay of tectonic loading, fault mechanics, and lithological heterogeneity in shaping cascading earthquake hazards in Central Sulawesi
Volcano‑tectonic seismicity and related hazard: a component of the multi‑hazard assessment in the highly exposed region of Mt. Etna (Italy)
Full text linkIn this study, seismic hazard, a component of the multi‑hazard assessment studied in the framework of the PANACEA project, was performed following the probabilistic approach (PSHA) based on historical macroseismic data. This approach uses intensity site observations to compute the seismic history for each investigated locality. Site seismic histories completeness are improved the integrating observed intensities with “virtual” values calculated according to attenuation laws, starting from the earthquake parameters (epicentre and epicentral intensity). The probability distribution of the expected intensities at a given site is calculated for exposure times of 10, 30 and 50 years. Results are given as reference intensity and peak ground acceleration for a chosen exceeding probability. In order to obtain hazard also in terms of expected peak ground acceleration (PGA) a relation between macroseismic intensity and ground acceleration calibrated for Mt. Etna was also developed. A PGA value was predicted for each intensity site observation using a specific ground motion model for Mt. Etna shallow events, assuming a soil class A. We tested the performance of the obtained relationship through synthetic and observed PGAs associated with the most energetic seismic eventinstrumentally recorded at Etna. Finally, the probability distribution for PGA at the site for a given exposure time results from the combination of the corresponding seismic hazard curve for the macroseismic intensity and the specific local intensity‑PGA relationship
Dynamics and hazards of pyroclastic avalanches at Etna volcano (Italy)
Full text linkWe present a multidisciplinary research aimed at quantifying the conditional probabilities for hazards associated with pyroclastic avalanches at Etna, which combines physical and numerical modeling of granular avalanches and probabilistic analysis. Pyroclastic avalanches are modeled using the depth-averaged model IMEX-SfloW2D, which is able to simulate the transient propagation and emplacement of granular flows generated by the collapse of a prescribed volume of granular material. Preliminary sensitivity analysis allowed us to identify the main controlling parameters of the dynamics, i.e. the total avalanche mass, the initial position of the collapsing granular mass (and the associated terrain morphology), the initial avalanche velocity, and the two rheological parameters which determine the mechanical properties of the flow. While the first two parameters can be considered as “scenario parameters” in the definition of the hazards, the initial velocity and the rheological parameters need to be calibrated. We therefore adopted a methodology for the statistical calibration of the physical model parameters based on field observations. We used data from the pyroclastic avalanche that occurred on February 10, 2022 at Etna, for which we had an accurate mapping of the deposit and some estimates of the total mass and the initial volume. We then run a preliminary ensemble of numerical simulations, with fixed initial volume and position, to calibrate the other input parameters. Based on the accuracy of the matching of the simulatedand observed deposits (measured by the Jaccard Index), we extracted from the simulation ensemble a subsample of equally probable combinations of initial velocities and rheological parameters. We then built an ensemble of model input parameters, with varying (i) avalanche volumes, (ii) initial positions, (iii) velocity, and (iv) rheological coefficients. The initial volume range was chosen within the range of observed pyroclastic avalanches at Etna (i.e., between 0.1 and 3 × 106 m3), using a prescribed probability distribution extracted from the literature data. The initial positions have been chosen on the flanks of the South East Crater of Etna, with homogeneous spatial distribution. The initial velocity and the rheological coefficients were chosen from the subsample created with the calibration. Finally, a semi-automatic procedure (digital workflow) running the Monte Carlo simulation allowed us to produce the first probabilistic map of pyroclastic avalanche invasion at Etna. Such a map, conditional to the occurrence of a pyroclastic avalanche event, can be used to identify the hazardous areas of the volcano and to plan mitigation measures