Rapid assessment of an earthquake’s impact on the affected society is a crucial step in the early phase of disaster management, determining the further organization of civil protection measures. In this study, we demonstrate that felt-reports containing macroseismic observations, collected via the LastQuake service of the European Mediterranean Seismological Center, can be utilized to rapidly estimate the probability of a felt earthquake to be “damaging” rather than “harmless” on a global scale. In our fully data-driven, transparent, and reproducible approach, we first map the reported observations to macroseismic intensities according to the EMS-98 macroseismic scale. Subsequently, we compare the distribution of felt-reports to documented earthquake impact in terms of economic losses, number of fatalities, and number of damaged or destroyed buildings. Using the distribution of felt-reports as predictive parameters and an impact measure as the target parameter, we infer a probabilistic model utilizing Bayes’ theorem and Kernel Density Estimation, that provides the probability of an earthquake to be “damaging”. For 22% of felt events in 2021, a sufficient number of felt-reports to run the model is collected within 10 minutes after the earthquake. While a clean separation of “damaging” and “harmless” events remains a challenging task, correct and unambiguous assessment of a large portion of “harmless” events in our dataset is identified as a key strength of our approach. We consider our method an inexpensive addition to the pool of earthquake impact assessment tools, that can be utilized instantly in all populated areas on the planet. Being fully independent of seismic data, the suggested framework poses an affordable option to potentially improve disaster management in regions that lack expensive seismic instrumentation today and in the near future.

How to cite: Lilienkamp, H., Bossu, R., Cotton, F., Finazzi, F., Landès, M., and Weatherill, G.: Utilization of crowdsourced macroseismic observations to distinguish damaging from harmless earthquakes globally within minutes of an event, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14699, https://doi.org/10.5194/egusphere-egu23-14699, 2023.

We propose a methodology to assist in the selection or definition of weights for components of seismic hazard models, which are combinations of seismic source models and ground motion models, in the context of probabilistic seismic hazard assessment (PSHA). The methodology uses Bayes's theory by optimally exploiting available observations that are the seismic catalogues and accelerometric databases. When compared to the current method of calculation, the proposed approach, simple to implement, allows a more exhaustive use of the data and discriminates between inputs without expert judgements to weigh branches of the PSHA logic tree.

We implement the proposed methodology in a Python package called Phebus to process the seismic source models (the first of the two main ingredients of the seismic hazard model) as a first step. The main purpose of this package is to estimate earthquake recurrence parameters and confidence intervals using a full Bayesian approach, and perform a Bayesian model averaging (BMA) amongst multiple seismic source models. More particularly, we focused our study on area-source models, which consist of subdivisions of a particular region of interest into zones that are assumed homogeneous in terms of seismic activity rate, and that are systematically used in PSHA calculations for low-to-moderate seismic regions. We conducted sensitivity analyses on the selection performances and the adjustments performances of recurrence parameters for simplistic toy models against a synthetic model-generated seismicity catalogue. We also illustrate the application of Phebus to the metropolitan France, a low-strain region, where at least four national, competitive and published area-source models are used by engineers and researchers for seismic hazard evaluation.

How to cite: Duverger, C., Keller, M., and Senfaute, G.: How to discriminate between area-source models for probabilistic seismic hazard assessment in a more objective manner?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7745, https://doi.org/10.5194/egusphere-egu23-7745, 2023.

On August 2021, 14^th, a Mw 7.2 earthquake struck Haiti’s southern peninsula, eleven years after the devastating Mw 7 January 12, 2010 earthquake that occurred near Port au Prince. This large event, called the Nippes earthquake, has been recorded locally by the citizen network composed of low-cost raspberry shake stations. A precise analysis of the mainshock rupture from geodetic and seismic data revealed both left lateral strike slip and trust motion.

Few days after the mainshock, a temporary network consisting of 12 broadband stations was deployed in the vicinity of the epicentral zone in order to better record the aftershock sequence. Data from August 20 to December 31, 2021, were used to determine a suitable 1D velocity model of the zone and relocate about 2500 aftershocks that highlight the activation of several structures.

In this study, we focus our analysis on the region of Miragoâne situated between the ruptures of the 2021 and the 2010 earthquakes.  Before the Nippes earthquake, only a few events were detected there. Then, the Nippes earthquake triggered a burst of seismicity that lasted two months and stopped on November 2, 2021 and resumed in January 14 until March 10, 2022 with the occurrence on January 24th of two earthquakes in less than an hour of magnitude 5.3 and 5.1 respectively. We use the new 1D velocity model and the NonLinLoc using Source-Specific Station Term Corrections method (NLL-SSST) to relocate this seismic sequence. We find that the two larger earthquakes of magnitude slightly greater than 5 are closely located and confirm their reverse faulting mechanism using the waveform inversion method FMNEAR. The relocated seismicity is distributed from the surface to 20 km deep between the coast and the Enriquillo left-lateral strike-slip fault and along a plane which dips southward at ~50°, in agreement with the reverse faulting mechanism of the two larger magnitude > 5 earthquakes.

How to cite: Paul, S., Monfret, T., Courboulex, F., Delouis, B., Deschamps, A., Douilly, R., Ambrois, D., Symithe, S. J., St Fleur, S., Calais, E., and Chèze, J.: The Miragoâne seismic clusters in southern Haiti triggered by the Mw 7.2 Nippes earthquake of August 14, 2021, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13526, https://doi.org/10.5194/egusphere-egu23-13526, 2023.

On May 22, 2021, a M_S7.4 earthquake occurred in Madoi County, Guoluo Prefecture, Qinghai Province. The epicenter was located at 98.34°E and 34.59°N (Officially determined by China Earthquake Networks Center). The earthquake occurred inside the Bayan Har block with a focal depth of 17 kilometers. The regional stress adjustment after a major earthquake directly causes the surrounding faults to undergo Coulomb stress changes, which affects the rate of seismic activity, off-fault aftershocks, and probability changes of occurrence of impending earthquakes. This paper uses the fault slip model to calculate Coulomb stress changes of main faults in Madoi area of Qinghai. Using the Dieterich earthquake occurrence rate model, a formula for the occurrence probability of an earthquake exceeding a certain magnitude under the Coulomb stress disturbance is obtained. We calculate the probability changes of M_S≥7.0 and M_S≥6.0 earthquake occurrence of the surrounding 8 faults (segments) which caused by the Coulomb stress increase. Affected by the Qinghai Madoi M_S7.4 earthquake, the probability of the 8 faults earthquake occurrence has increased to varying degrees. For the Gander South Margin fault, Madoi-Gander fault and Tibet Dagou- Changmahe fault, the probability of earthquakes occurrence has increased rapidly in a short period of time (within about 10 years) after the main shock and it has stabilized later. There is a potential for destructive earthquakes, especially for earthquakes with M_S≥6.0. For the Dari fault, since the increase in Coulomb stress has little effect, it is unlikely to occur M_S≥7.0 or M_S≥6.0 in the short term. However, as time goes by, the possibility of potentially destructive earthquakes occurring decades later cannot be ruled out. Particular attention to the possibility of earthquakes with M_S≥6.0 should be paid to. The East Kunlun fault, especially the Maqin-Maqu section, is still a possible section for strong earthquakes in the future. This section still needs to focus on and prevent earthquakes with M_S≥6.0 and even M_S≥7.0. An earthquake with M_S≥6.0 occurred on the Yushu-Ganzi fault, especially the risk of an earthquake with M_S≥7.0 is not high, while the Ulan-Ula Lake-Yushu South fault has a potential risk of destructive earthquakes. It is necessary to strengthen prevention for earthquakes with M_S≥6.0.

How to cite: Liu, B.: Effect of Qinghai Madoi MS7.4 earthquake on Coulomb stress and earthquake probability increment of adjacent faults, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17388, https://doi.org/10.5194/egusphere-egu23-17388, 2023.

The knowledge of the crustal stress field is essential in the evaluation of the seismic hazard of an area.To this aim, it is necessary to derive reliable focal mechanisms mainly when small earthquakes have to be included in the computation. The first motion focal mechanism solution techniques are still widely used in modern softwares. The determination of P-wave polarities with manual procedures can lead to human errors and it is time-consuming. Automatic procedures can avoid these drawbacks. Polarity identification is not a classification task easily expressed in terms of mathematical procedures, in fact classical automatic procedures can lead to worse results than those obtained by human operators. For this reason, the use of machine learning approaches results necessary to accomplish this task.With low computational costs, real-time analysis capabilities, no need for complicated pre-processing procedures, and truly competitive results, properly designed convolutional networks can be the answer to various problems, including those related to seismology. 

In our work, we present the Convolutional First Motion (CFM) network, a Deep Convolutional Neural Network (DCNN) used to classify seismic traces based on first motion polarities of P-waves. We used waveforms contained in two datasets. We prepared the first dataset selecting approximatively 150˙000 waveforms contained in the Italian seismic catalogue INSTANCE, specifically designed for the application of machine learning techniques. To this end we devised an analysis procedure using Principal Component Analysis and Self-Organising Maps, through which a clustering process individuated groups of suitable traces. A second dataset, not specifically designed for machine learning techniques, is prepared manually picking approximatively 4˙000 waveforms of earthquakes occurred between 2010 and 2014 at Mt. Pollino area in Italy, avoiding possible overlapping of waveforms between the two datasets. The network, trained on ~130˙000 time windows centred on P-wave arrival times of waveforms in the INSTANCE catalogue, achieved accuracies of 95.7% and 98.9% on two test sets: the Mt. Pollino dataset and part of the INSTANCE catalogue. Further testing showed that if we give the network waveforms with uncertain arrival times, it acquires robustness to this type of noise, still showing high-level of performance.

We infer that the CFM network would be suitable in succession to automatic techniques that derive P-wave arrival times, for example techniques in which deep learning is used, in order to cover the entire data processing phase with machine learning. Given the incredible ability of DCNNs to model and process large volumes of data and their remarkable performance, it is reasonable to assume that deep learning will soon become the norm even in the context of first-motion polarity determination. 

This work was partially supported by the PRIN-2017 MATISSE project (no. 20177EPPN2), funded by the Ministry of Education and Research.

How to cite: Messuti, G., Scarpetta, S., Amoroso, O., Napolitano, F., and Capuano, P.: CFM: a Convolutional network for First Motion polarity classification of earthquake waveforms., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5751, https://doi.org/10.5194/egusphere-egu23-5751, 2023.

Surface wave arrival angles are an important secondary set of observables to constrain Earth's 3-dimensional structure. These data have also been used to refine information on the alignments of horizontal seismometer components with the geographic coordinate system. In the past, particle motion has been inspected and analyzed on single 3-component seismograms, one at a time. But the advent of large, dense seismic networks has made this approach tedious and impractical. Automated toolboxes are now routinely used for datasets where station operators cannot determine the orientation of a seismometer upon deployment, such as conventional free-fall ocean bottom seismometers. 

In a previous paper, we demonstrated that our automated Python-based toolbox DLOPy compares favorably with traditional approaches to determine instrument orientations. But an open question has been whether the technique also provides  individual high-quality measurements for an internally consistent dataset to be used for structural imaging. For this feasibility study, we compared long-period Rayleigh-wave arrival angles at frequencies between 10 and 25 mHz for 10 earthquakes during the first half of 2009  that were recorded at the USArray Transportable Array (TA), a component of the EarthScope program. After vigorous data vetting, we obtained a high-quality dataset that compares favorably with an arrival angle database compiled using our traditional interactive screen approach, particularly at frequencies 20 mHz and above. 

On the other hand, the presence of strong Love waves may hamper the automated measurement process as currently implemented. 
While the proper choice of the start time of the analysis window may depend on a particular geographic location of a seismic network, our observations for USArray data suggest that a slightly later start time than is currently used may yield more high-quality Rayleigh wave measurements.

How to cite: Laske, G., Frazer, W., and Doran, A.: Benchmarking Automated Rayleigh-Wave Arrival Angle Measurements for USArray Seismograms, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9201, https://doi.org/10.5194/egusphere-egu23-9201, 2023.

The Korea Meteorological Administration(KMA) uses seismic and infrasound networks data identifying  explosion, collapse, and earthquakes.
We identify events using various methods . First, Vp/Vs spectral amplitude ratio in the frequency domain is calculated by applying Fast Fourier Transform (FFT) and Power Spectrum Density (PSD) analysis methods. The Vp/Vs ratio more than 50% is distinguished as an explosion.
Second, Explosion, collapse, and earthquakes are distinguished by (using) the body wave method (Walter et al., 2018). The Pn/Lg, Lg/Lg ratios are used for studying the DPRK 6th test, collapse and induced earthquakes at Chuncheon, Sokcho, and Seohwa KMA seismic networks.
Finally, the KMA operates five infrasound networks for  monitoring DPRK nuclear test and Mt. Baekdu volcano in addition to the seismic networks.
Infrasound analysis calculates the apparent speed and azimuth of the infrasound source by applying Progressive Multi-Channel Correlation(PMCC)  algorithm.
The calculated azimuth and apparent velocity are  important factors in determining that the seismic and infrasound signals occurred at the same point during an explosion.

How to cite: Min, K., Choi, M., You, S., Choi, Y., Chai, G., and Park, S.: A Study on the Identification of Explosions, Collapses and Earthquakes using KMA Seismic and Infrasound Networks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4855, https://doi.org/10.5194/egusphere-egu23-4855, 2023.

In this work, we present a new earthquake catalogue for metropolitan France (i.e. the part of France located in Europe), which can be used to derive parameters of interest for seismic hazard modeling in that region. The catalogue is built from the amalgamation of existing catalogues for France but also neighboring countries, for both historical (here, ante-1965) and instrumental times. It covers a period ranging from 250 to 2020. Magnitudes are homogenized as moment magnitudes (Mw) using adequate conversion laws when needed. Uncertainties on location and magnitude are also provided so they can be used to realistically quantify epistemic uncertainties in hazard models. This catalogue somehow represents an updated version of the catalogue used in Drouet et al. (2020), augmented from recently published information. It extends from -8.1°E to 11.°E in longitude and from 38°N to 51°N in order to encompass the three area source models that were used in that study. The core of this catalogue is FCAT-17 (Manchuel et al., 2018), completed using the most recent ESHM2020 catalogue, FCAT-17 being given priority on the French territory plus a 20 km buffer beyond its borders and exclusive economic zone. Then, national catalogues for neighboring countries (Portugal, Spain, United Kingdom, Ireland, Belgium, Netherlands, Luxembourg, Germany, Austria, Switzerland, Italy) are also incorporated and are given full priority over their territory. The final model contains more than 45,000 events with magnitudes as low as Mw=2.0. Such low magnitudes were considered in order to provide as much constraint as possible to recurrence models, despite the fact low magnitude events are -per se- of little interest for seismic hazard models.

How to cite: Arroucau, P., Drouet, S., Daniel, G., Traversa, P., and Manchuel, K.: A new earthquake catalogue for seismic hazard assessment in metropolitan France and neighboring countries, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9542, https://doi.org/10.5194/egusphere-egu23-9542, 2023.

The Czech Republic is situated in an intraplate region with low seismicity. The seismic hazard is relatively low but not negligible. A new map of the seismic hazard of the Czech Republic computed using a probabilistic approach is being compiled and will be released in the second half of 2023. As a part of this project new catalogues of earthquakes, both historical (based on macroseismic observations) and instrumental (based on seismograms) were compiled. These include earthquakes on the territory of the Czech Republic and neighboring areas of Slovakia, Austria, Germany and Poland.
       When analyzing these new enhanced catalogues, we recognized a period of increased seismicity at the beginning of the 20th century. The annual seismicity rate in this time interval for earthquakes with a magnitude 4 and greater is several times higher than at present. One possible explanation is the inconsistent magnitude determination between the beginning of the 20th century and the present time. Therefore, we re-examine historical seismograms at the beginning of the 20th century and verify their magnitudes. We also compared macroseismic observations of historical earthquakes with modern ones having almost the same magnitude.
       We found out that the increased seismicity at the beginning of 20th century is real. During this period, relatively large earthquakes were observed in various source zones in the investigated region. Such earthquakes have not occurred since 1920-1930 to the present. 

How to cite: Fojtíková, L., Málek, J., Prachař, I., Lukešová, R., Kysel, R., Vackář, J., Valenta, J., and Lachová, B.: Increased seismicity at the beginning of 20th century in the Czech Republic and adjacent areas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11857, https://doi.org/10.5194/egusphere-egu23-11857, 2023.

The Maltese archipelago lies in the centre of the Sicily Channel (Central Mediterranean), a crustal domain subject to extension since the Miocene and characterised by the presence of several active graben systems in the Plio-Quaternary. This region is affected by diffuse seismicity, in the form of isolated swarms interspersed with long pauses of quiescence and events of modest magnitude, in general not exceeding 4.0. The key features of seismicity are poorly constrained by unfavourable geographical conditions and the scarcity of seismic stations in the area between southern Sicily and Tunisia. Until a few years ago, the only Maltese station operating (WDD of the MedNet network) was the only source of information to characterise local Maltese seismicity. On the other hand, the localisations of major events (M > 4) made by the other monitoring agencies (e.g. Istituto nazionale di Geofisica e Vulcanologia - INGV) are based on traveltime readings from seismograms recorded at great distances from Malta (> 100 km) and are therefore affected by considerable formal errors. Moreover, the only published catalogue of offshore seismicity around the Maltese islands (Seismic Monitoring and Research Group, University of Malta) is based on single station location at WDD up to 2014. This is characterised by considerable uncertainties in hypocentral parameters, in particular a lack of depth information. In consequence, therefore, it is very difficult to obtain information on the geometry and kinematics of active tectonic structures, both offshore and possibly on.

In recent years, there has been a considerable increase in the number of seismic stations on the Maltese archipelago: there are currently eight active stations, that make up the Malta Seismic Network (MSN). The study we present is an example of the application of 3-D localisation techniques of Maltese seismicity, which benefits from the recent implementation of the local seismic network. In particular, we focus on the swarm occurring offshore in the period September-October 2020, and characterised by an unusual number of events (> 100), including a main event (M > 4.0) that was strongly felt over the archipelago. We have handpicked P- and S-wave traveltimes for all the events using recordings from the MSN and a selected number of Italian stations according to quality criteria, and inverted them using the Hypoellipse code. The precise earthquake localisations allow us to obtain details of the structures activated during the swarm, together with a more detailed insight into the time evolution of the sequence. Accompanying these analyses, we calculated the moment tensor solutions for some of the largest events (M > 3) and performed a spectral analysis to distinguish the waveform characteristics of events occurring at shallow depths (< 10 km) from those nucleating in the mid-crust (> 15 km depth), as a function of different wavepaths through the crust. The prospect is that in the future it will be possible to better constrain the seismotectonics of the Maltese archipelago and have a more accurate picture of the seismogenic potential of active faults in this sector of the Mediterranean.

How to cite: Caricato, C., Galea, P., Baccheschi, P., Tinti, E., Villani, F., Agius, M., and D'Amico, S.: Recent improvements in seismic monitoring of the Maltese archipelago: A case study from the 2020 seismic swarm., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12078, https://doi.org/10.5194/egusphere-egu23-12078, 2023.

The North Anatolian Fault (NAF) is a right-lateral continental transform fault that extends from eastern Anatolia to the northern Aegean in the eastern Mediterranean. It is characterized by strong and frequent seismic activity, posing a high seismic hazard level to the region. The Main Marmara Fault (MMF), the northern branch of the NAF along the Marmara Sea (NW Turkey), has produced several major earthquakes (M7+) in the past with a recurrence rate of about 250 years. At present, there is a 150 km seismic gap along the MMF that has not ruptured since 1766. The MMF seismic gap shows distinct variability in its along-strike interseismic strain-accumulation with locked and creeping segments, but it is unclear which are the controlling parameter of this observation. Thus, the interseismic evolution of the MMF, especially its frictional state and its inter-to-pre-seismic behavior, is still a matter of debate. It has been proposed that the observed along-strike variation in strain localization around the MMF might be linked to a heterogeneous off-fault crustal and sedimentary rheological configuration.

Here, we use a forward numerical approach with visco-elastic rheology to investigate the space and time scales of the long-term seismic behavior of the Main Marmara Fault and its main controlling factors. The MMF is modelled following a Coulomb frictional constitutive law. The spatially variable rock properties are derived from a lithospheric-scale 3D structural model of the region around the MMF. This model has been generated with a data-driven approach in a previous stage of the work. The forward model is used to test the effect of varying boundary conditions (i.e. kinematic) and fault strength properties (i.e. coefficient of friction). Our modelling approach highlights the first order role of crustal rheology and fault-strength in the long-term behavior of the MMF (spatial distribution and recurrence of seismic events), as well as their potential to explain the along fault locking degree variability.

How to cite: Fernandez, N., Cacace, M., Scheck-Wenderoth, M., and Heidbach, O.: Factors influencing the long-term interseismic behavior of the Main Marmara Fault, NW Turkey, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13752, https://doi.org/10.5194/egusphere-egu23-13752, 2023.

At volcanic islands, seismometers are the main tool for monitoring various active processes including seismicity that could forewarn impending eruptions. However, the sparse seismic networks, high background noise levels, large diversity of seismic signals, and high event rates during unrest episodes make automatic detection and classification of volcano seismicity a difficult challenge. In this paper, we use the Alaska Volcano Observatory’s catalogue of ~120,000 long-period (LP) and volcano-tectonic (VT) earthquakes at 34 volcanoes from 1989-2018 to evaluate the efficacy of automatic detection and classification methods. For each event, we calculate the frequency index (FI) based on the ratio of mean spectral amplitudes in the higher and lower frequency bands of the recorded waveforms. Using the local minima in the FI distribution at each volcano as the classification boundary, we find that our labels generally agree with the catalogue’s manual labels. The classification boundaries separating LP and VT earthquakes are also relatively consistent (FI = -1) between volcanoes. Therefore, the FI method is an effective method for automatic classification of volcano seismicity. We then evaluate the performance of two machine-learning-based models (PhaseNet and EQTransformer) and the cross-correlation-based template-matching method for automatic detection. While the template-matching method is computationally more expensive, we find that most of the catalogue events can be detected by using another event as a template, with relatively low false positive rates. In comparison, both machine-learning-based models’ performances are worse than previously reported results and deteriorate systematically with decreasing FI index values. The bias might have resulted from the models having been trained using earthquake catalogues from non-volcanic regions that lack LP events. Therefore, these models should be retrained with a dataset of volcano seismicity before being applied for automatic earthquake detection at volcanic regions.  

How to cite: Tan, Y. J., Song, Z., and Zhong, Y.: Efficacy of automatic detection and classification methods for volcano seismicity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11450, https://doi.org/10.5194/egusphere-egu23-11450, 2023.

In retreating subduction zones the proposed lithosphere tearing processes at slab edges are typically related to segmentation of subducting plate. A direct response to lithosphere tearing is the channeling of new asthenospheric mantle that can initiate magmatism. Tearing mechanisms have also been proposed for the Calabrian Arc, where slab migration led to the formation of the southeastern Tyrrhenian basin and was progressively accommodated by inherited and newly formed vertical tear faults whose oldest (~2 Ma) and youngest (~0.8 Ma) tectonic expressions in the upper plate are the Sisifo-Alicudi and the Aeolian-Tindari-Letojanni fault systems, respectively. The Western and Central-Southern Aeolian Islands nested along these structures as highlighted by a large number of geological and geophysical studies in the last decades. CAVEAT aims to apply a multidisciplinary approach to study in detail the local lithospheric structure, the pattern of crustal deformation and the geochemical signature of the Central-Southern Aeolian Islands. The acquisition of new data will provide a broad overview of the ongoing geodynamics of the southern Tyrrhenian region and will allow us to properly study the interplay of present-day tectonics and volcanic deformation and the related role and nature of the fluids and the hydrothermal activity.

How to cite: Scognamiglio, L., Palano, M., Di Luccio, F., Pezzo, G., De Gregorio, S., and Greco, F. and the CAVEAT Team: Volcanism and tearing in the Tyrrhenian subduction system: the CAVEAT project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9184, https://doi.org/10.5194/egusphere-egu23-9184, 2023.

The Vulcano-Lipari System is a volcanic complex located in the central sector of the Aeolian Archipelago in southern Italy. The edifice is affected by complex tectonics and develops upon the trans-extension of the Aeolian-Tindari-Letojanni Fault System. This fault is proposed to control magmatism and acts as a preferential pathway for upwelling of magmatic and supercritical fluids. Over the last three decades, Vulcano Island underwent several volcanic crises and since September 2021 it has been showing signs of increasing activity and volcanic unrest. Temperature, degassing, seismic activity, and deformation rapidly increased causing temporal evacuation of the inhabitants of the most affected regions. During the unrest in October 2021, we deployed 196 3C geophones all around Vulcano and south of Lipari to record the seismic signals for a full month, as part of the VulcaNODES project. The resulting seismic catalog confidently contains more than 7000 volcano-seismic and volcano-tectonic events with an average local magnitude of -0.32. This catalog is used to produce an unprecedented travel-time time-lapse tomography of the unrest. Seismic tomography is a powerful tool for observing structures at depth beneath volcanic systems, using seismic waves generated by earthquakes. Such a dense network combined with the exceptional seismic signal recorded will provide tomographic time series of the plumbing system every 1-3 days for a month. The still ongoing VulcaNODES project aims at observing fluids evolution along the volcano’s tectonic structures on a daily basis, providing new insights on processes usually difficult to record on short timeframes, and shedding light on the plumbing system on a high resolution.

How to cite: Barat, C., Savard, G., Muñoz, F., Stumpp, D., Alparone, S., Ricci, T., Ursino, A., Palano, M., Reyes Hardy, M.-P., Pruiti, L., Planes, T., Sparacino, F., Bonadonna, C., Ruch, J., Caricchi, L., and Lupi, M.: Deployment of dense nodal network during unrest: investigation of the Vulcano-Lipari System (Italy) with Local Earthquake Tomography, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11359, https://doi.org/10.5194/egusphere-egu23-11359, 2023.

Seismic tomography represents a very powerful and effective tool to look at depths beneath volcanic systems thus helping to better understand their behavior. In particular, a key parameter useful to discriminate the presence of gas, fluids and melts is represented by the P-wave and S-wave velocity ratio. In the present study, we collected ~ 4400 crustal earthquakes that occurred in the last thirty years and we used the LOcal TOmography Software LOTOS to estimate the first 3D overall model of Vp, Vs and Vp/Vs for the Lipari–Vulcano complex belonging to the Aeolian islands system (southern Tyrrhenian sea). The investigated area has been characterized both in old and recent times by fumaroles, hydrothermal activity and active degassing. In particular, in the past decades several episodes of anomalous increases of fumarole temperature and strong degassing have interested the Vulcano Island, the latter of which started in September 2021.

The results of the tomographic investigation indicate the presence of two main anomalies of low Vp and low Vp/Vs, clearly depicted up to ~ 8 km depths, and related to gas-rich materials beneath the central-northern sector of Vulcano and the western off-shore of Lipari, respectively.

The anomaly beneath Vulcano is located in close correspondence with La Fossa caldera area and with the sector where fumaroles, hydrothermal activity and active degassing are widely documented. Moreover, beneath the western Lipari off-shore a new, previously undetected, volume of strong gas-concentration has been identified. Even if these two anomalies show almost the same intensity, no evidence of degassing activity is available for the latter one because of its location at sea depths where the relevant water column pressure may inhibit the observation of possible degassing processes.

The obtained results furnished a picture of the spatial distribution of gas-filled volumes feeding the main degassing activity of the Lipari-Vulcano complex and allowed to highlight the main role played by volcanic gas in the whole system, thus furnishing invaluable constraints for improved modelling of the volcanic system and of its possible evolution.

How to cite: Totaro, C., Aloisi, M., Ferlito, C., Orecchio, B., Presti, D., and Scolaro, S.: Seismic tomography investigation at the Lipari-Vulcano complex (South Italy) provides new insights on the active degassing system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12460, https://doi.org/10.5194/egusphere-egu23-12460, 2023.

We present the analysis of the local and regional seismicity recorded in 2019-2021 by a temporary seismic network installed on Terceira Island. This new seismic dataset allow us to study the induced seismicity caused by fluid extraction in a geothermal powerplant and to image the subsurface seismic structure with local earthquake tomography. 

From the distribution of the seismicity, it is possible to highlight two regions with a high number of events amongst other areas. The first one, located in the central part of the island, is associated with the volcanoes of Pico Alto and Guilherme Moniz, with  low magnitude earthquakes, and hypocentre's depths less than 10 km. The geothermal power plant is located in the transition between these two volcanic systems. We identify a cluster of earthquakes in the neighbourhood of the geothermal power plant at depths ranging from 1 to 3 km, consistent with the induction by the powerplant operation. The second seismicity region is located on the island's western sector, at the Santa Bárbara volcanic system. There, the seismicity pattern is more complex, mainly by the occurrence of both tectonic and seismo-volcanic earthquakes.  

Local earthquake tomography allows imaging of the crust from the surface to the upper-middle crust, up to 8 km depth. The Santa Bárbara and Pico Alto volcanoes are characterized by low Vp and high Vp/Vs anomalies, stronger in the first and typically related to active volcanoes. In the transition between the two volcanoes, we observe shallow strong Vp and very low Vp/Vs anomalies typical of geothermal fields. On the other hand, the Guilherme Moniz volcano exhibits high Vp anomaly and normal Vp/Vs values.

The eastern sector of the Terceira is characterized by low seismicity and, consequently, low tomographic resolution. 

This work is a contribution to projects GEMMA (PTDC/CTA-GEO/2083/2021) and RESTLESS (PTDC/CTA-GEF/6674/2020), and it was also supported by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020-IDL, UIDB/04683/2020 - ICT and UIDP/04683/2020 - ICT

How to cite: Fontiela, J., Afonso Dias, N., Silveira, G., Moreira, M., and Matias, L.: Seismicity and crustal structure of the Terceira Island, Azores, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14189, https://doi.org/10.5194/egusphere-egu23-14189, 2023.

Volcanic eruptions are, generally, characterized by several recordable signals that can occur before, during and/or after the eruption. Such signals may reflect temporal changes in the seismic structure that can be associated with alterations in the seismic activity, fluid migration or outgassing, useful to track the volcano evolution through its eruptive phases.

Cumbre Vieja ridge, in La Palma, is the most active volcanic field in the Canaries. The last eruption occurred at the Tajogaite cone, lasting from 19 September to 13 December 2021. It is considered one of the best-monitored volcanic crises in the Canary Islands, thus allowing us to study the eruption from different scientific perspectives.

Ambient seismic noise interferometry has been widely applied to monitor temporal velocity changes, especially at volcanoes before the eruption. However, the causes of these velocity changes are not always fully understood. In this study we use a dataset of three years (2020 to 2022) recorded in two stations operating in La Palma to identify and characterize different physical processes before and after the eruption. For this purpose, we computed phase auto- and cross-correlations and stacked them through the time-frequency phase-weighted stack to create hourly cross-correlation functions.

Seismic velocity changes cause phase shifts in the auto- and cross-correlation functions waveforms. The phase shifts can be measured through the waveform similarity, which consists in comparing each correlation function with a reference correlation function trace, in a defined window. The reference trace corresponds to a calm period, in this case, the period before the eruption. We also compared the waveform similarity results with the ground deformation inferred from GPS.

Tajogaite eruption provides an opportunity to study the behaviour within the volcanic structure prior to the eruption and its recovery after the eruption and to improve our knowledge of the magmatic fluid migration. This recent and well-documented eruption may serve as a proxy for future eruptions.

This work is a contribution to project RESTLESS (PTDC/CTAGEF/6674/2020) and it was also supported by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020-IDL.

How to cite: Carvalho, J., Silveira, G., Bento, V., Schimmel, M., and Antón, R.: Insights into the fluid migration dynamics of Tajogaite eruption, La Palma, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9245, https://doi.org/10.5194/egusphere-egu23-9245, 2023.

The quality of the earthquakes’ catalogs plays the most important role in the study of seismicity, of active faults, in seismic hazard and risk assessment, etc. The quality of the catalog is evaluated by the absence of duplicate records or explosions in itself. For example, in catalogs of historical earthquakes, often the same earthquake, described by different historical sources, appears as two different earthquakes. The situation is much more complicated in instrumental catalogs, where often tremors of the surface of the earth's crust related to human vitality appear as natural earthquakes.

The study of the instrumental earthquakes’ catalogs using daily histograms and remote sensing methods made it possible to identify a large number of events that, in our opinion, are not natural earthquakes. In particular, the catalog of The International Seismological Center (ISC), on the territory of Northern Kazakhstan and South-East Russia, contains more than 10,000 events that are most likely explosions, and not earthquakes. Likewise, the catalog of the National Survey for Seismic Protection of Armenia (NSSP) in the region of the Armenia-Georgia border contains more than 1,000 events that are also explosions. Similar events were recorded in Spain, Egypt, Turkey, Syria.

The used methodology for the detection of false earthquakes is recommended for cleaning the instrumental catalogs of seismic events.

How to cite: Davtyan, V., Kazarian, A., and Kazarian, H.: Certain problems related to earthquakes’ catalogs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9358, https://doi.org/10.5194/egusphere-egu23-9358, 2023.