SM1.1 | General Contributions on Earthquakes, Earth Structure, Seismology
EDI
General Contributions on Earthquakes, Earth Structure, Seismology
Convener: Alice-Agnes Gabriel | Co-convener: Philippe Jousset
Orals
| Fri, 19 Apr, 08:30–12:25 (CEST)
 
Room -2.47/48
Posters on site
| Attendance Fri, 19 Apr, 16:15–18:00 (CEST) | Display Fri, 19 Apr, 14:00–18:00
 
Hall X1
Orals |
Fri, 08:30
Fri, 16:15
The session General Contributions on Earthquakes, Earth Structure, Seismology features a wide range of presentations on recent earthquakes and earthquake sequences of local, regional, and global significance, as well as recent advances in characterization of Earth structure using a variety of methods.

Orals: Fri, 19 Apr | Room -2.47/48

The oral presentations are given in a hybrid format supported by a Zoom meeting featuring on-site and virtual presentations. The button to access the Zoom meeting appears just before the time block starts.
08:30–08:35
08:35–08:45
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EGU24-7660
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SM1.1
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On-site presentation
Andreas Steinberg, Nicolai Gestermann, Lars Ceranna, Gernot Hartmann, Björn Lund, Eric Dunham, Patrick Hupe, Peter Voss, Tine Larsen, Trine Dahl-Jensen, Andreas Köhler, Johannes Schweitzer, Christoph Pilger, Thomas Plenefisch, Klaus Stammler, Stefanie Donner, Peter Gaebler, and Christian Wiedle

On 26 September 2022 two seismic events near the Danish island of Bornholm in the Baltic Sea were detected. The first event with a magnitude Mw 2.3 occurred at 00:03 UTC 40 km east-southeast of Bornholm. The determined location and the origin time of the event are consistent with data of the pressure decrease on one of the Nord Stream 2 pipelines. Another sequence of events occurred 17 hours later at 17:03 UTC around 60 km north-east of Bornholm with a maximum magnitude of Mw 2.7. It consists of three closely successive, but separable, single events. Using relative localisation methods and the gas pressure inside the pipeline recorded at the landing site in Germany, we can assign the epicentres of the three events to the locations of the leaks in the pipelines of Nord Stream 1 and 2.

Based on comparable events in the region, which include both tectonic earthquakes and explosions, the explosive character of the investigated Nord Stream events can be verified. Infrasound signals associated with the destruction of the Nord Stream pipelines were recorded at two stations (I26DE in the Bavarian Forest and IKUDE near Kühlungsborn) in Germany. Particularly after the event sequence at 17:03 UTC, distinctive signals were registered whose characteristics indicate an explosive event with subsequent gas leakage at the surface.

Our modelling of the sources shows that the measured seismic signals can sufficiently be explained by the instantaneous gas release. Synthetic seismograms for such a source and a subsurface model adapted for the study area show high consistency with the measured signals. Based on the released energy and the characteristics of the recorded waveforms, we conclude that the impulsive gas release from the burst gas pipes constitutes the dominant part of the signal source. The model places an upper limit of approximately 50 kg TNT equivalent on the yield of the chemical explosive component of the events, but we note that smaller yields may also be consistent with the data.

We also carried out an analysis of the seismic signals of the event on the Balticconnector pipeline between Finland and Estonia on 8 October 2023 and found that again the instantaneous gas release can sufficiently explain the observed data. This supports a possible mechanical cause of the damage.

 

How to cite: Steinberg, A., Gestermann, N., Ceranna, L., Hartmann, G., Lund, B., Dunham, E., Hupe, P., Voss, P., Larsen, T., Dahl-Jensen, T., Köhler, A., Schweitzer, J., Pilger, C., Plenefisch, T., Stammler, K., Donner, S., Gaebler, P., and Wiedle, C.: Source analysis of the 2022 Nord Stream and 2023 Balticconnector underwater explosions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7660, https://doi.org/10.5194/egusphere-egu24-7660, 2024.

08:45–08:55
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EGU24-8482
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SM1.1
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ECS
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On-site presentation
Gizem Izgi, Eva P.S. Eibl, Frank Krüger, and Felix Bernauer

Six-degree-of-freedom (6-DoF) measurements, which combine rotational sensors and seismometers, provide a comprehensive dataset that allows seismologists to determine the back azimuth of a potentially moving source from a single-point measurement. Our investigation focused on tracking the movement of a vibroseis truck operating from 20 November 2019, 11:00 UTC, to 21 November 2019, 14:00 UTC. Using 480 sweep signals, each lasting 15 seconds and covering a wide frequency range from 7 to 120 Hz, we measured at 160 different locations. Back azimuths for each sweep were derived from the 6-DoF data, and root mean squares were calculated for each component. This procedure was repeated for five additional rotational sensors of the same type.
During the first day, the north component of all sensors recorded larger amplitude signals than the East and Vertical, indicating the dominance of SV (shear-vertical) wave energy. Subsequently, we observed gradually increasing amplitudes on the east component, which was consistent with the direction of the moving vibroseis truck. Although the dominant wave type recorded was SV, and the method of comparing horizontal rotation rates was used to calculate the back azimuth, we observed a relatively decreasing accuracy of direction estimates as the truck moved away from the sensors due to increased scattering. To fully understand the reason for this, we investigated the specific fingerprint of each wave type in the wave field. Our results suggest that direction estimates should be made using only the portion of the wavefield containing SV-type waves when using this method, and then the moving source should be tracked accordingly. This approach provides insight into the trajectory of the truck and improves our understanding of the seismic signals generated during the experiment.

How to cite: Izgi, G., Eibl, E. P. S., Krüger, F., and Bernauer, F.: Tracking a Vibroseis Truck and Investigating the Wavefield using 6 Rotational Sensors in Fürstenfeldbruck, Germany , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8482, https://doi.org/10.5194/egusphere-egu24-8482, 2024.

08:55–09:05
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EGU24-1985
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SM1.1
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On-site presentation
Angela Stallone, Jacopo Selva, Louise Cordrie, Licia Faenza, and Alberto Michelini

Seismic urgent computing aims at assessing the potential impact of earthquakes through rapid simulation-based ground-shaking forecasts. However, uncertainty quantification remains a significant challenge in this domain.

While current practice accounts for the uncertainty arising from Ground Motion Models (GMMs), it neglects the uncertainty about the source model, which is only known approximately in the first minutes after an earthquake. Addressing this issue involves propagating earthquake source uncertainty from a multi-scenarios ensemble that captures source variability to ground motion predictions. In principle, this could be accomplished with 3D modelling of seismic wave propagation for multiple earthquake sources. However, full ensemble simulation is unfeasible under emergency conditions with strict time constraints.

Here we present ProbShakemap, a Python toolbox which generates multi-scenario ensembles and delivers ensemble-based forecasts for urgent source uncertainty quantification. It implements GMMs to efficiently propagate source uncertainty from the ensemble of scenarios to ground motion predictions at a set of points, while also accounting for model uncertainty (by accommodating multiple GMMs, if available) along with their intrinsic uncertainty. Notably, ProbShakemap does not rely on any recorded data, and only requires the following event-specific information: latitude, longitude, magnitude and time. ProbShakemap incorporates functionalities from two open-source toolboxes routinely implemented in seismic hazard and risk analyses: the USGS ShakeMap software and the OpenQuake-engine.

We quantitatively test ProbShakemap against past earthquakes, illustrating its capability to rapidly quantify earthquake source uncertainty.

How to cite: Stallone, A., Selva, J., Cordrie, L., Faenza, L., and Michelini, A.: ProbShakemap: a Python toolbox for urgent earthquake source uncertainty quantification, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1985, https://doi.org/10.5194/egusphere-egu24-1985, 2024.

09:05–09:15
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EGU24-1310
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SM1.1
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On-site presentation
Mungunsuren Dashdondog, Odonbaatar Chimed, Anne Meltzer, and Ankhtsetsteg Dorjsuren

The purpose of the study is to describe a geodynamic process in the study area using its focal mechanism and stress field inversion to characterize precise events along the study area, the rupture zones of the South Hangay Fault System (SHFS). This fault system was activated by four earthquakes which are occurred along the Bayanbulag fault (2012/10/03, Mw=4.7) and Bayankhongor fault (2013/01/05, Mw=4.2, & Mw=4.2; 2013/11/25, Mw=3.9). These earthquakes are the strongest in the fault zone.

From the Mongolian National Data Center's database, it has chosen 2228 occurrences (0.1ML5.4) from the Handay Experiments, which used 72 broadband seismometers to cover Hangay Dome. Using HypoDD with a double-difference technique, its seismic station density provides us with precise hypocenter location along the fault system. Among these events, 47 focal mechanism solutions were determined using the first-motion polarity of the P wave from the experimental seismic networks of Mongolia. Then, we classified the determined focal mechanism parameters. According to classification, three main cluster zones are related to the Bayanbulag (BB), Bayankhongor North (BHN), and Bayankhonor South (BHS) fault zones along the rupture area of the South Hangay Fault System. 

Furthermore, we determined the stress fields, stress regime, and the horizontal maximum (SHmax), and minimum (Shmin) stress orientations for all three zones.  

We concluded that the whole SHFS is a left-lateral strike-slip fault with normal and reverse components, NE-SW shortening, and corresponding NW-SE extension. Its compression orientation in the NE-SW direction is the same as the azimuth direction of the India-Asia collision.

We hope that this stress inversion results can be a useful tool for geodynamic and seismotectonic analysis of this part of Mongolia and it will give a better understanding of different stress regimes.

How to cite: Dashdondog, M., Chimed, O., Meltzer, A., and Dorjsuren, A.: The seismic source parameters of the South Hangay Fault System in Central Mongolia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1310, https://doi.org/10.5194/egusphere-egu24-1310, 2024.

09:15–09:25
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EGU24-17485
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SM1.1
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ECS
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Virtual presentation
Sayan Bala, Abhisek Dutta, and Chandrani Singh

In this study, we have evaluated the scattering nature of the crust beneath the Bhutan Himalaya, located in the eastern part of the Himalayan arc. We have analysed high-quality waveforms of 566 events having magnitude (ML) below 6, recorded by broadband stations of the GANSSER network operated by the Swiss Seismological Service at ETH Zurich from Jan, 2013 to Nov, 2014. We have investigated the peak delay time (tpd), defined as the time interval between the initial S-wave appearance and the peak amplitude of its envelope, for the frequency ranges of 4–8, 6–12, 8–16 and 12–24 Hz. Initially, we have analysed frequency-dependent nature of tpd at 9 stations (BHE01, BHE09, BHE13, BHN02, BHN06, BHN11, BHW01, BHW10 and BHW16). The observed values of Bfreq, which indicates the frequency dependence of the peak delay time, show mostly low positive values up to 0.3. It shows that tpd is independent of frequency which may be associated with the relative proportions of large as well as small scale heterogeneities present in the mediumAt BHE09, Bfreq exhibits a negative value, which might be attributed to the limited sampling of high-frequency signals that capture small portions of the subsurface along their paths. The crust beneath BHE09 experiences reduced scattering, probably due to the absence of a strongly attenuating body in the subsurface. Furthermore, we aim to extend this study for all the stations and to compare the frequency-dependent nature of T5%-75% (time interval between 5% and 75% of the total integrated power value) and the tpd for the study region.

How to cite: Bala, S., Dutta, A., and Singh, C.: Frequency-dependent delay time analysis for Bhutan Himalaya, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17485, https://doi.org/10.5194/egusphere-egu24-17485, 2024.

09:25–09:35
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EGU24-20056
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SM1.1
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ECS
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Virtual presentation
Zamir Khurshid, Hamzeh Mohammadigheymasi, Dawei Gao, Jianxin Liu, and S. Mostafa Mousavi

Seismic networks monitor seismic activities across the globe, recording distinctive events within specific geographical and temporal frames. Whether old or new, each seismic record preserves valuable information, with its extraction relying mainly on the sophistication of the method. This study presents the implementation of an advanced earthquake detection workflow on a relatively old dataset, the Bhutan Pilot Experiment. This temporary five-station seismic network in Eastern Himalaya comprised a set of Broadband sensors deployed for 14 months from January 2002 to March 2003. However, outdated methodologies have limited the analysis of the recorded data, resulting in the reporting of only 175 local microearthquakes in this area. In this study, we reprocess the data using the recently introduced deep-scan Integrated Pair-Input deep learning and Migration Location workflow [1] to detect and locate local earthquakes. The IPIML employs the well-known Earthquake Transformer (EqT) model as its core function for initial phase picking, followed by a pair-input Siamese EQTransformer (S-EqT) to further mitigate the false negative rate using a pair-wise model. The S-EqT step demonstrated an approximately 40% increase in average detected phases compared to the standard EqT model. The detected phases are associated using the Rapid Earthquake Association and Location (REAL) method through grid searching, providing a preliminary list of detected events. This list encompasses 2458 detected events, several times larger than the previously reported catalog for this dataset. These events primarily cluster in central and eastern Bhutan, particularly along the Golpara lineament, a recognized strike-slip fault. The subsequent phase of this study involves precisely locating these events through the implementation of the Migration Location (MIL) method.

References
[1] H. Mohammadigheymasi et al., "IPIML: A Deep-Scan Earthquake Detection and Location Workflow Integrating Pair-Input Deep Learning Model and Migration Location Method," in IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-9, 2023, Art no. 5914109, doi: 10.1109/TGRS.2023.3293914.

How to cite: Khurshid, Z., Mohammadigheymasi, H., Gao, D., Liu, J., and Mousavi, S. M.: Deep Scanning of the Bhutan Eastern Himalaya Seismic Dataset for Local Earthquakes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20056, https://doi.org/10.5194/egusphere-egu24-20056, 2024.

09:35–09:45
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EGU24-4004
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SM1.1
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ECS
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On-site presentation
Qiwen Zhu, Nobuaki Fuji, and Li Zhao

The collision of the Indian and Eurasian plates has resulted in high-altitude Tibetan Plateau with active seismicity. In this study, we apply the seismic box tomography to the southern Tibetan Plateau, aiming to obtain a self-consistent and high-resolution (10−20 km) model of the crust and upper mantle beneath the region, including density as well as bulk and shear moduli without a priori constraints, which provides us with crucial constraints on the compositional and thermal structures of a highly deformed lithosphere in southern Tibetan Plateau.

In order to obtain the seismic tomographic model, we perform full-waveform inversion of teleseismic (30°−90°) surface- and body-wave waveforms recorded by the Hi-CLIMB network, a densely distributed (5−10 km station spacing) N-S oriented linear seismic array deployed during 2002 and 2005. In our iterative hierarchical inversion workflow, we calculate the sensitivity kernels based on the adjoint method and the model is updated by the L-BFGS algorithm. Data covariance matrices are introduced to control the data quality and objective weighting functions for different seismic events. We will present our preliminary results of the on-going study with comparison to existing models.

How to cite: Zhu, Q., Fuji, N., and Zhao, L.: Full-waveform tomography for the lithospheric structure of southern Tibetan Plateau, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4004, https://doi.org/10.5194/egusphere-egu24-4004, 2024.

09:45–09:55
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EGU24-8852
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SM1.1
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Virtual presentation
Hamzeh Mohammadigheymasi, Zhuowei Xiao, S. Mostafa Mousavi, Mohammadreza Jamalreyhani, Jaime Almeida, and Nuno M. Garcia

This abstract presents the findings of a comprehensive seismicity analysis conducted in Ghana using the advanced Deep-Scan workflow [1]. The study compiled data from 461 earthquakes, revealing new insights into active seismogenic sources in this relatively under-explored region. A more accurate crustal velocity model is computed, and the detailed Green functions for focal mechanisms of detected events are estimated. Data integration from a single Ivory Coast station improved the azimuthal coverage of hypocenters, facilitating more precise velocity model estimations for deeper layers. The study utilized 5213 accurately picked arrival phases from 284 earthquakes, applying joint inversion techniques to optimize crustal velocity and hypocentral parameters. This resulted in a detailed 6-layer model, with P-wave velocity values ranging from 5.6 to 6.3 km/s and a high-velocity layer at 7.8 km/s, maintaining a consistent Vp/Vs ratio of 1.70. Analysis of the earthquakes revealed six compact clusters, predominantly aligned with the Akwapim fault zone and linked to the active section of the Romanche fracture zone in Axim. The distribution of hypocentral depths consistently falls within the range of 9-18 km, confined to the upper crust of the region. Utilizing the revised velocity model notably enhanced the identification of the seismogenic zone in southern Ghana. Moreover, it facilitated the generation of detailed Green functions for the next step for moment tensor (MT) inversion of small-magnitude earthquakes, employing a bootstrap-based probabilistic inversion schema. The results enhance our understanding of Ghana’s seismicity and represent key points for hazard and risk assessment in the region. This research is supported by Funda¸c˜ao para a Ciˆencia e Tecnologia (UIDB/00645/2020 and https://doi.org/10.54499/UIDB/00645/2020, and UIDB/50008/2020).

References
[1] H. Mohammadigheymasi et al., "IPIML: A Deep-Scan Earthquake Detection and Location Workflow Integrating Pair-Input Deep Learning Model and Migration Location Method," in IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-9, 2023, Art no. 5914109, doi: 10.1109/TGRS.2023.3293914.

How to cite: Mohammadigheymasi, H., Xiao, Z., Mousavi, S. M., Jamalreyhani, M., Almeida, J., and M. Garcia, N.: Enhanced insight into Ghana's Seismicity through a Refined Crustal Velocity Model and Earthquake Focal Mechanisms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8852, https://doi.org/10.5194/egusphere-egu24-8852, 2024.

09:55–10:05
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EGU24-9598
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SM1.1
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ECS
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Highlight
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On-site presentation
Asaf Inbal

Seismic waves excited by human activity frequently mask signals due to tectonic processes, and are therefore discarded as nuisance.  Seismic noise-field analysis is, however, a powerful tool for characterizing anthropogenic activities. Here, I apply this analysis to examine seismic precursors to the October 7 Hamas attack on Israel. The precursory activity in Gaza included massive mobilization which took place in the hours leading to the attack, and was  documented on multiple media outlets. Favourable conditions, which arise due to a temporary lack of anthropogenic activity in Israel, allow remote seismic stations to record signals due to Gaza vehicle traffic. I use these seismograms in order to identify anomalous ground-motions, associate them with pre-attack mobilization, and precisely determine their location. By applying array analysis to three seismic stations located tens-of-kilometers from the Gaza strip, I was able to obtain valuable information on the Hamas attack plans. This suggests that embedding seismic noise-field analysis into decision-making protocols could enhance preparedness, thus providing an opportunity to blunt terrorist attacks and reduce the number of casualties.

How to cite: Inbal, A.: Seismic Precursor for the October 7th Terrorist Attack?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9598, https://doi.org/10.5194/egusphere-egu24-9598, 2024.

10:05–10:15
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EGU24-8735
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SM1.1
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Highlight
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On-site presentation
Bettina Goertz-Allmann, Ben D.E. Dando, Andreas Koehler, Quentin Brissaud, Johannes Schweitzer, and Tormod Kværna

Apart from classical earthquake monitoring, seismological data can also be used to detect explosions in near-real-time on both regional and global scales. We demonstrate how seismic and infrasound data can provide more comprehensive and objective information about conflict-related explosions or suspicious events that might be the result of targeted attacks. We can identify the underwater explosions at the Nord Stream pipeline infrastructure in the Baltic Sea in September 2022. Cross-correlation analysis allowed us to identify sub-events several seconds apart which can be associate with specific locations along the pipelines. Furthermore, we detect a signal at the Finish seismic array in October 2023 which may be associated with the damage along the Balticconnector. The other example is from Ukraine, where we present the ability to automatically identify and locate ground explosions related to the Russia-Ukraine conflict with data from the Malin array (AKASG). Between February and November 2022, we observe more than 1,200 explosions from the Kyiv, Zhytomyr, and Chernihiv provinces. Both seismic and infrasound detections can be used to verify and improve accurate reporting of military attacks and help to provide an unprecedented view of an active conflict zone. We analyze events with a variety of seismo-acoustic signatures and significant differences in explosive yield. These can be associated with various types of military attacks, including artillery shelling, cruise missile attacks, airstrikes, or the destruction of the Kakhovka dam NE of Cherson.

How to cite: Goertz-Allmann, B., Dando, B. D. E., Koehler, A., Brissaud, Q., Schweitzer, J., and Kværna, T.: Near-real time detection of conflict-related explosions or suspicious events using seismological data , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8735, https://doi.org/10.5194/egusphere-egu24-8735, 2024.

Coffee break
10:45–10:55
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EGU24-15494
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SM1.1
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On-site presentation
Luca C. Malatesta, Shigeru Sueoka, Kyoko S. Kataoka, Tetsuya Komatsu, Sumiko Tsukamoto, Lucile Bruhat, and Jean-Arthur Olive

On January 1st 2024, a Mw 7.6 earthquake shook the Noto Peninsula on the Sea of Japan coast of Central Japan causing over 202 casualties and >100 missing (at the time of submission). The quake follows a period of intensifying seismic activity starting in 2020. The Mw 6.3 Oku-Noto earthquake of May 5 2023 was the previous largest event of the sequence. The Jan. 1 2024 Noto Peninsula earthquake significantly impacted the Peninsula. A large number of landslides and rockfalls dissected the road network. Liquefaction damaged infrastructure up to 150 km away from the epicenter. Meter-scale coseismic uplift modified the northern shoreline with displacement of the coastline by up to 200 m seaward discernible on SAR and aerial image data. At the time of abstract submission (Jan. 10 2024) we only have limited preliminary observations. It appears that the Noto Earthquake ruptured the same or adjacent fault to the May 5 2023 Mw 6.5 earthquake and was in the vicinity of the March 25 2007 Mw 6.9 Noto earthquake. Coseismic displacement measured geodetically shows uplift of up to +3–4 m (SAR) in the northwest of the peninsula (Wajima-shi), and +1.06 m (GPS) in the main town of Wajima-shi. The uplift magnitude decreases gradually to the SE. The uplift is near zero (SAR) or -0.3 m (GPS) on Noto Island (Nanao-shi) 30 km to the south of the town of Wajima. Surface deformation goes back to near zero (GPS) a further 20 km to the south.

The coseismic deformation pattern broadly reflects the deformation recorded in the Noto landscape. Long-term moderate rock uplift in the north gives way to a complex history of long-term slow uplift around Noto Island that likely includes sustained episodes of subsidence, highlighted by its sinuous “drowned” coastline. Along the western shore (Shika-machi), marine terraces presumed to be 120 ka (last Interglacial) show a gradient in elevation also decreasing to the south. In the north, the newly emerged platform does not have a higher marine terrace counterpart. This may reflect the relationship between high wave power and moderate rock uplift resulting in the long-term retreat of the coastline and erosion of any terrace. The Noto Peninsula also holds widespread evidence of drainage reorganization that would reflect varying boundary conditions, in particular rock uplift, in deeper time beyond 100’s ka. The similarities between recent landscape morphology and coseismic displacement suggest that the Jan. 1 2024 rupture fits a recent pattern of crustal strain in Noto Peninsula (at least up to 100 ka). Earlier deformation pattern (>100’s ka) likely happened along different faults and/or at different rates as reflected by the transient drainage network.

By conference time, we will present field observations collected after the rescue and emergency work is completed.

How to cite: Malatesta, L. C., Sueoka, S., Kataoka, K. S., Komatsu, T., Tsukamoto, S., Bruhat, L., and Olive, J.-A.: Geology and geomorphology of the Jan 1st 2024 Mw 7.6 Noto Peninsula Earthquake: observations and context., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15494, https://doi.org/10.5194/egusphere-egu24-15494, 2024.

10:55–11:05
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EGU24-13903
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SM1.1
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ECS
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On-site presentation
Sambuddha Dhar, Youichiro Takada, and Jun Muto

Seismicity records during the 1990’s reveals that large inland earthquakes tend to concentrate near several active volcanoes in the central part of northeastern (NE) Japan (Hasegawa & Yamamoto, 1994 Tectonophysics). The inland seismicity around active volcanoes could be related to localized zones of high strain contraction detected by the GNSS measurements in 1997–2001 (Miura et al., 2004 JGR). Several studies speculated that the localized strain contraction is caused by inelastic deformation of weak lithosphere beneath the active volcanoes (Hasegawa et al., 2004 J. Seismol. Soc.). Such weak lithosphere (i.e., low-viscosity zone or LVZ) is inferred from high heat-flow observations (Tanaka et al., 2004 EPS), lithospheric strength simulation (Shibazaki et al., 2016 GRL; Muto, 2011 Tectonophysics) and seismic-velocity tomography (Hasegawa et al., 2005 JGR). However, because of complex interplay between elastic and inelastic processes during steady-state (i.e., interseismic) crustal deformation, the physical mechanism related to inelastic deformation is still poorly understood.

When the Mw9.0 2011 Tohoku-oki earthquake occurred, strong surface deformations were observed locally near the active volcanoes (Takada & Fukushima, 2013 Nat. Geosci.) and continued for several years after the mainshock (Muto et al., 2016 GRL). Past studies (e.g., Sun et al., 2014 Nature) advocated that the earthquake-related inelastic processes such as viscoelastic mantle relaxation dominates the crustal deformations in the postseismic period. In the present study, we identified localized strain contractions near the active volcanoes by extracting the short-wavelength strain rate (Meneses-Gutierrez & Sagiya, 2016 EPSL) from the GNSS observations during 2012–2014. We explained these localized strain contraction by building three-dimensional rheological models of small-scale LVZs beneath five active volcanoes of NE Japan. We simulated the volumetric deformation of viscoelastic LVZs using power-law Burgers rheology, which previously succeeded to explain the large-scale postseismic deformation of the 2011 Tohoku-oki earthquake (Agata et al., 2019 Nat. Commun.; Muto et al., 2019 Sci. Adv.; Dhar et al., 2022 GJI). The power-law Burgers rheology represents the bi-phasic nature of rock deformations (rapid transient with subsequent steady state) and power-law dependency of strain rate to evolving stress (proxy of dominating dislocation creep in high-stress mantle condition) (Muto et al., 2019 Sci. Adv. and references therein).

We found that the localized strain contraction near the active volcanoes can be explained by small-scale LVZs which have narrow tops of 10–20 km and wide roots of 60–100 km width. Our results conclude the minimum depths of the tops and roots of LVZs are 15 km and 40 km, respectively. The geometries of the LVZs vary (e.g., upright conic or inclined shape) from volcano to volcano. The effective viscosities of the LVZs are in the order of 1017 Pa·s immediately after the earthquake and increases to the order of 1018 Pa·s over the 3 years of postseismic deformation. Our results agree with the results of several past studies (Ohzono et al., 2012 EPS; Hu et al., 2014 EPS; Muto et al., 2016 GRL) who investigated the lithospheric rheology near Mt. Naruko using the postseismic surface displacements of the 2011 Tohoku-oki and 2008 Iwate-Nairiku earthquakes.

How to cite: Dhar, S., Takada, Y., and Muto, J.: Rheology of weak lithosphere beneath active volcanoes of NE Japan: Insights from postseismic deformation of 2011 Tohoku-oki earthquake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13903, https://doi.org/10.5194/egusphere-egu24-13903, 2024.

11:05–11:15
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EGU24-15942
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SM1.1
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On-site presentation
Susanna Falsaperla, Giovanni Barreca, Ornella Cocina, and Salvatore Spampinato

Numerous episodes of volcanic unrest have taken place at Vulcano island (Italy) since its last Vulcanian eruption occurred 133 years ago. Decades-long seismic monitoring has documented some of them. We have collected and examined all available seismic data recorded since 1985, most of which were in analog format and/or dispersed in old repositories. We were able to compile catalogs where three different types of seismic events are considered according to their location and magnitude: events in the Fossa Crater, in the Lipari-Vulcano complex, and earthquakes with M>2.5. The primary goal of this data collection was to identify the main features of seismic activity on and around the island in the 36 years preceding the last volcano unrest, which began in mid-September 2021 with a high occurrence frequency of Very Long Period (VLP) events. Our review of the past seismic activity allows us to contextualize the newly recorded anomalous variations. Furthermore, we sought the connection with the structural framework of the region.

The duration of the episodes of volcanic unrest in 1985 and 1988 was relatively short (lasting just a few months) when compared to the recent one, which ended in December 2023. The source of the seismic events during those past unrests was mainly close to the reference station (now IVCR) with hypocenters mostly beneath the island at shallow crustal depths (up to 5 km below sea level). Their magnitude remained low (<2.5) during both the episodes (i.e., 1985, and 1988).

Overall, the seismicity recorded in and around the island has reached a maximum value of M4.6 both in the 36 years preceding and during the 2021 unrest. Some preliminary insights can be drawn by comparing the seismicity occurred during past and recent unrest episodes: i) the peculiarly long duration of the most recent unrest, and ii) the importance of broadband equipment, which documented the substantial contribution of VLP seismicity during the 2021-2023 episode.

How to cite: Falsaperla, S., Barreca, G., Cocina, O., and Spampinato, S.: Insights into the 36 Years of Seismic Activity at Vulcano Island, Italy, preceding the Volcanic Unrest in 2021, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15942, https://doi.org/10.5194/egusphere-egu24-15942, 2024.

11:15–11:25
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EGU24-9479
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SM1.1
|
On-site presentation
Mickaël Bonnin, Marion Alloncle, Maxime Bes de Berc, Éric Beucler, Damien Fligiel, Marc Grunberg, Céline Hourcade, Clément Perrin, Olivier Sèbe, Jérôme Vergne, and Dimitri Zigone

On June 16, 2023 at 16h38 UTC, a moderate earthquake of magnitude MW=4.9 stroke western France south of Niort city, near the small village of La Laigne (Charente Maritime). The shaking has been widely felt in the whole NW France and macroseismic intensity (EMS98) of VII was reached at the epicenter. Such an event is relatively rare in continental France and represents the second largest event in the western France in the last century. The epicentral region is located at the northern termination of the Aquitaine basin where 300 m of Mesozoic sediments covers the variscan basement. The focal mechanism obtained from waveform inversion corresponds to a pure dextral strike-slip motion or a pure senestrial strike-slip motion along a EW or NS striking fault plane, respectively.

The fault that ruptured on June 16 is not known. To gain insight on its characteristics, teams of Nantes (Osuna and LPG), of Strasbourg (EOST and ITES) and of the CEA deployed between June 17 and June 22, 2023 for approximately one month, a network of 3-components stations composed of 12 MEMS accelerometers, 104 five hertz geophones and 5 broadband velocimeters in a 40 by 30 km region around the epicenter, with a station inter-distance of approximately 4 km.

We present is this study the first results derived from this unique experiment. In particular, we show that the aftershock sequence (more than 600 events recorded) highlights a planar rupture zone of about 5.4 km2, trending NS and strongly dipping to the East (75°), located between 2 and 5 km depth. Site effect analysis allows us to better understand large ground motion distributions over the area and their link with macroseismic intensities. The installed array also allows us to infer a preliminary 3D VS model of the region. We show the extent to which a dense temporary network is mandatory for studying the fine structure of the fault plane in a region where previous knowledge of active geological structures is limited.

How to cite: Bonnin, M., Alloncle, M., Bes de Berc, M., Beucler, É., Fligiel, D., Grunberg, M., Hourcade, C., Perrin, C., Sèbe, O., Vergne, J., and Zigone, D.: Aftershock sequence and source characteristics of the June 16, 2023 MW=4.9 La Laigne earthquake, western France, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9479, https://doi.org/10.5194/egusphere-egu24-9479, 2024.

11:25–11:35
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EGU24-1533
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SM1.1
|
ECS
|
On-site presentation
Marion Alloncle, Antoine Mocquet, and Mickaël Bonnin

The seismic moment M0, the associated moment magnitude Mw, and the corner frequency fc are essential parameters for earthquake studies and seismic risk management. In the context of stable continental regions (SCRs), remote from active plate boundaries, the assessment of these parameters is made difficult by the low energy release associated with each earthquake and the low density of seismological networks.

In the north west of France, the Armorican Massif and its surroundings are part of a SCR, where the densification of the seismological network, completed in 2019, now allows for a reassessment of the regional seismicity. Though characterized by very small strain rates, the region currently displays a high rate of low-to-moderate earthquakes (up to a few Mw lower or equal to 4.0 – 5.0). For such small earthquakes, these assessments are particularly sensitive to the signal-to-noise ratio, to the seismic structure of the region, to its attenuation properties, and to the azimuthal distribution of the regional network with respect to the focal mechanisms.

We attempt to determine the M0, and the fc, of 106 earthquakes, detected in northwestern France between 2015 and 2023, with local magnitudes ML ranging from 2.0 to 5.3, using spectral methods. We obtained a linear relationship between ML and Mw for Mw ranging from 1.5 to 5.0. Our analysis also highlighted the importance of the frequency dependence of attenuation on the assessment of the fc. This study will show the relation between M0 and fc in the region.

How to cite: Alloncle, M., Mocquet, A., and Bonnin, M.: Earthquake source characterization in stable continental regions: Application to the Armorican Massif, France, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1533, https://doi.org/10.5194/egusphere-egu24-1533, 2024.

11:35–11:45
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EGU24-11960
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SM1.1
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ECS
|
On-site presentation
Gabriele Tarchini, Daniele Spallarossa, Stefano Parolai, Denis Sandron, and Angela Saraò

In the early morning of 23 February 1887, the ‘Ligurian earthquake’, a devastating seismic event currently estimated at MW 6.3-7.2, shook the towns of the Italian and French Riviera. It is the most devastating earthquake known in this region: it is thought to have claimed at least six hundred lives, displaced twenty thousand people, and destroyed many historic buildings and houses. As a result of the event, a tsunami with a maximum run-up of two meters near Imperia (Italy) also occurred and the record of the tide gauge in the port of Genoa (Italy) has long been considered the only existing record of the event.

However, we found that the 1887 earthquake was also recorded by historical magnetometers in the UK and France. These instruments were used to measure variations in geomagnetic field strength, but were also able to record seismic waves, which were essentially a simple ‘disturbance’. Almost uninterrupted records of this type of variometric data are held by the British Geological Survey (BGS). Traces recorded at Greenwich, Kew, and Falmouth magnetic observatories, which clearly show waveforms related to the event, were used. The Bureau Central de Magnetisme Terrestre (BCMT) also keeps magnetograms: in particular, we used the recordings of the instrument at Le Parc de Saint-Maur (Saint-Maur-des-Fossés, Paris).

The waveforms were digitized and processed according to the theory of Eleman (1966), which describes the response of a classical declinometer and/or a horizontal force instrument to harmonic ground displacement, and according to the work of Krüger et al. (2018).

The location of the epicenter and the magnitude of this historical earthquake are difficult to characterize with high accuracy, and the focal mechanism of the fault responsible for the event remains controversial to this day. We present the preliminary results of our research, which is focused on the revaluation of the Ligurian earthquake in terms of magnitude and focal mechanism. This would lead for the first time to a definition of magnitude on an instrumental basis for this important seismic event, whose macroseismic intensity is usually assessed based on studies conducted immediately after the event to determine the damage it had caused.

How to cite: Tarchini, G., Spallarossa, D., Parolai, S., Sandron, D., and Saraò, A.: Reassessment of the historical earthquake of 23 February 1887 in Liguria (north-western Mediterranean) on the basis of magnetogram recordings, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11960, https://doi.org/10.5194/egusphere-egu24-11960, 2024.

11:45–11:55
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EGU24-12990
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SM1.1
|
On-site presentation
Michael Perlin, Neil Trerice, Ted Somerville, and Marian Jusko

Geophysical monitoring requires the highest level of performance and reliability from purpose-built and tightly integrated instrumentation and infrastructure. Parallel and separate efforts between different scientific disciplines seen in the past came at the expense of duplicated infrastructure, telemetry and power subsystems, and even land use permits. This duplication increases costs, ultimately limiting station counts and reducing “the reach” of monitoring networks. Recent ambitions to combine multi-disciplinary geophysical applications into streamlined deployments led to initiatives such as the European Plate Observing System (EPOS) and the recent amalgamation of the SAGE and GAGE programs in the United States.

Modern seismic dataloggers, such as the Nanometrics Centaur, support a wide range of seismo-acoustic sensor interfaces and sensor types while maintaining ultra-low power consumption, precise timing, and reliable data transport with automatic back-fill features over flexible telemetry mediums. These properties transformed the Centaur’s capabilities to act as a highly versatile foundation in multi-disciplinary geophysical station deployments. 

Despite initially being designed as a high-performance data recorder for seismic applications, Centaur’s applicability has evolved to include data collection for the infrasonic, geodetic, magnetic, and meteorological domains. This triggered the development and addition of purpose-built features to support multi-disciplinary use cases with the same proven performance and reliability of a Centaur seismic station.

Both existing and planned capabilities that enable reliable and efficient multi-disciplinary science are discussed.

How to cite: Perlin, M., Trerice, N., Somerville, T., and Jusko, M.: Seismic Network Station Infrastructure as the Basis for Multi-Disciplinary Geophysical Stations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12990, https://doi.org/10.5194/egusphere-egu24-12990, 2024.

11:55–12:05
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EGU24-4895
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SM1.1
|
On-site presentation
Ruey-Juin Rau, Cheng-Feng Wu, Ying-Chi Chen, Hung-Yu Wu, and Chin-Jen Lin

We used the liquid-based R2 rotational seismometer in addition to several arrays of translation velocity seismometers on a 12-floor building in the National Cheng Kung University campus to evaluate the dynamic responses of the structure. During the observation period in August-October 2023, we encountered a moderate M 5.6 earthquake sequence 61 km north of the campus and one moderate typhoon passing through this 49-m-long and 12-m-wide building. By examining these data, we investigate the natural frequency and the rotation behavior of the long-strip-shaped building. Both the time-frequency and Fast Fourier Transform analyses of the microtremor and earthquake data show two dominant frequencies of ~1.2 Hz and 1.8 Hz occurred in the horizontal directions. The translation velocity and rotation rate are more significant in the transverse, short-axis direction and at the location away from the elevator of the building. The translation velocity array and rotational seismometer show rotations around the horizontal and vertical axes during the M 5.6 earthquake. The results of two natural frequencies and the corresponding rotational motions are most likely related to the asymmetric design of the building, which resulted in the non-rigid behavior of the structure. These findings may provide insights into improvements that could enhance the building’s resilience to seismic or typhoon events.

How to cite: Rau, R.-J., Wu, C.-F., Chen, Y.-C., Wu, H.-Y., and Lin, C.-J.: Dynamic responses of a building derived from microtremor and seismic signals, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4895, https://doi.org/10.5194/egusphere-egu24-4895, 2024.

12:05–12:15
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EGU24-749
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SM1.1
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ECS
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On-site presentation
Berkan Özkan, Tuna Eken, Peter Gaebler, and Tuncay Taymaz

For decades, the seismological community has debated the scaling relationships of earthquake sources. The debate centers around whether the scaled energy (ER/M0) remains uniform across all magnitudes, indicating self-similarity, or if there is an increase in scaled energy with seismic moment, M0. To contribute to this discussion, we analyzed coda derived source displacement spectra of 303 local earthquakes that occurred in and around the segments of the North Anatolian Fault Zone (NAFZ) within the Sea of Marmara. Our database includes digital waveform recordings of the events that were occurred between 2018 and 2020 (2.5≤ ML ≤5.7 within a radius of 200 km) and were recorded at 49 seismic stations operated by the Kandilli Observatory and Earthquake Research Institute (KOERI) in the study area. We employed a joint inversion technique to optimize source-, path-, and site-specific factors simultaneously. This was achieved by comparing the observed coda envelope with its physically derived representative synthetic coda envelope based on Radiative Transfer Theory. Our inversion process, conducted across various frequency bands, enabled us to make reliable coda-based seismic moment (M0) and moment magnitude estimates (Mw-coda) consistent with local catalogue magnitudes. The variation of the scaled energy (ER/M0) calculated from the total seismic radiated energy (ER) using coda-derived source displacement spectra for each event tends to increase with seismic moment across most magnitude ranges. This indicates that the crustal earthquakes with Mw-coda 2.5 and Mw-coda 5.7 in this laterally heterogeneous region are likely to follow non-self-similarity. Our findings imply different rupture dynamics working for large earthquakes than small ones and relatively more efficient seismic energy radiation for larger earthquakes along the northwestern part of the NAFZ.

How to cite: Özkan, B., Eken, T., Gaebler, P., and Taymaz, T.: Implications for Non-Self Similar Energy and Moment Scaling of Small-to-Moderate Earthquakes Along the NAFZ: Source Displacement Spectra Derived from Coda Waves, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-749, https://doi.org/10.5194/egusphere-egu24-749, 2024.

12:15–12:25
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EGU24-17715
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SM1.1
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ECS
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On-site presentation
Elif Türker, Ming-Hsuan Yen, Marco Pilz, and Fabrice Cotton

The North Anatolian Fault Zone in Turkey spans 1400 km, passing through densely populated areas, including Düzce, which experienced the destructive Mw 7.2 event in 1999 that caused more than 700 lives. On 23 November 2022, for the first time in over 20 years, a moderate Mw 6.1 earthquake struck the city and surrounding area. Despite its moderate magnitude, the event caused unexpectedly severe damage to numerous buildings, as reported by local institutions (Disaster and Emergency Management Presidency; AFAD). Recognizing the potential impact of near-field effects such as ground motion pulses and directivity effects, which are known to increase damage in the vicinity of the fault, we investigate these phenomena using the AFAD-Turkish Accelerometric Database. Our analysis delves into the spatial distribution of ground motion intensities, revealing higher peak ground velocities in certain azimuthal ranges than predicted by existing ground motion models. Surprisingly, our findings challenge outcomes derived from previous studies, suggesting that impulsive ground motions associated with directivity effects mainly occur on the fault-normal component of large-magnitude events. In contrast, our examination of near-fault recordings indicates a concentration of velocity pulses, primarily on the fault-parallel component, and thus questions the widely established understandings of earlier studies.

How to cite: Türker, E., Yen, M.-H., Pilz, M., and Cotton, F.: Importance of Pulse-Like Ground Motions and Directivity Effects in Moderate Earthquakes based on the 23 November 2022, Mw 6.1 Gölyaka-Düzce Earthquake (Turkey)., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17715, https://doi.org/10.5194/egusphere-egu24-17715, 2024.

Posters on site: Fri, 19 Apr, 16:15–18:00 | Hall X1

The posters scheduled for on-site presentation are only visible in the poster hall in Vienna. If authors uploaded their presentation files, these files are linked from the abstracts below, but only on the day of the poster session.
Display time: Fri, 19 Apr 14:00–Fri, 19 Apr 18:00
X1.71
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EGU24-169
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SM1.1
Nato Jorjiashvili, Ia Shengelia, Tea Godoladze, Irakli Gunia, and Dimitri Akubardia

Georgia is situated in the Caucasus region, which is one of the most seismically active regions in the Alpine-Himalayan collision belt. Analysis of the historical and instrumental seismology of this region shows that it is still of moderate seismicity. The seismicity of the area reflects the general tectonics of the region.

Recently, number of seismic stations and earthquake records in Georgia significantly increased. Thus, we can run more detailed studies regarding ground motion prediction. 

Ground motion prediction equations (GMPEs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. In this study ground motion prediction equations are obtained by classical, statistical way, regression analysis. Also, new data and new features such as local soil conditions, fault types, etc. were considered for analysis. In the study models are obtained for PGA (horizontal and vertical), 5%-damped pseudo-absolute-acceleration spectra (SA) are described for periods between 0.01 s and 10 s (for both vertical and horizontal components).

Next stage was to assess the standard deviation and its minimization. Fuzzy Analysis gives a possibility of making optimal decision when available data is insufficient and cannot represent real situation. In our case it is quite difficult to explain all physical processes related to earthquakes. However, it is very important to consider all processes during the hazard assessment. Also, during GMPE assessment it is very difficult to consider site effect very precisely because available data is still insufficient. In this case usage of Fuzzy Analysis is the best solution. We constructed membership functions based on shear wave velocity measurements for each site class. Site classifications were done according to Eurocode8. At the end a significant reduction of uncertainties (~30-40%) was observed.

How to cite: Jorjiashvili, N., Shengelia, I., Godoladze, T., Gunia, I., and Akubardia, D.: Dealing with uncertainties related to ground motion prediction models for Georgia, Caucasus Region., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-169, https://doi.org/10.5194/egusphere-egu24-169, 2024.

X1.72
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EGU24-2254
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SM1.1
Ia Shengelia, Nato Jorjiashvili, Tea Godoladze, and Albert Buzaladze

Georgia is located in the Caucasus between The black and the Caspian seas and is surrounded by the Greater and Lesser Caucasus. Among the seismic areas of Georgia, the volcanic upland of Javakheti situated in the south of Georgia is notable for its high level of seismicity where three large earthquakes with M6 occurred in the last century. The main goal of the study is to investigate the attenuation properties of the lithosphere in the region using a hundred and twenty local earthquakes in 2008-2020  recorded at five seismic stations equipped with broadband Guralp CMG40T and Trillium 40  seismometers. Earthquake magnitudes varied from 1.5 to 4.1; epicentral distances and depth were smaller than 60 km and 19 km, respectively. The quality factors of coda waves Qcand direct P, S waves Qp,and Qs have been estimated using the single back-scattering model and the extended coda normalization methods, respectively. Wennerberg’s approach has been used to estimate intrinsic Qi and scattering Qs attenuation parameters. The Q values were fitted to a  power-law, of form Q(f)= Q0 (f)n, where Q0 is the quality factor at 1Hz and n is the frequency relation parameter, which depends on the heterogeneity of the medium. The obtained values of Qc, Qp, Qs, Qi, andQsc show the frequency-dependent character in the frequency range of 1.5-24 Hz and are expressed as:

Qc = (47.6±3.8)(1.034±0.048)Qp = (17.4±2.3)𝑓(1.100±0.033), Qs = (28.8±3.3)𝑓(1.048±0.039)

Qi = (62 ± 4) f (0.969±0.052),  Qsc = (177 ± 6) f (0.932±0.051)

The calculated attenuation parameters characterize the entire earth's crust under the Javakheti plateau and the surrounding area. The observed Qc and Qi values are almost identical at different central frequencies and both of them are less than Qsc. This means that the effect of intrinsic attenuation is dominated by scattering attenuation. Comparison of our results for similar lapse times to those obtained in other tectonic and seismic active regions show that the Q values and their frequency-dependent relationships are in an interval of values of tectonically active and highly heterogeneous regions. The results obtained will be useful for source parameter estimation, ground motion prediction, and hazard assessment of the study regions.

How to cite: Shengelia, I., Jorjiashvili, N., Godoladze, T., and Buzaladze, A.: Qc, Qp, Qs, Qi, and Qsc attenuation parameters in the southern part of Georgia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2254, https://doi.org/10.5194/egusphere-egu24-2254, 2024.

X1.73
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EGU24-2853
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SM1.1
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ECS
Xiaoyan Zhao, Youjin Su, and Lingyuan Meng

Based on the catalog of 225 earthquakes with magnitudes 5 or above, the catalog of earthquake sequences, and the focal mechanism of the historical earthquakes in Sichuan-Yunnan region from 1966 to 2021, and referring to the previous research and practice on the estimation of the tendency of the aftershock activity, 10 sample datasets for the judging features of the earthquake sequence types have been constructed. According to the earthquake sequences types—swarm type, mainshock-aftershock type, as well isolated type—three labels have been made. After processing the imbalanced state and the missing state of the feature parameters, a decision tree model was used to study and analyze the importance of feature parameters. The results showed that there were differences in the importance categories of the feature parameters in different periods. As the sequence data increased, sequence type judgment relied more on dynamic sequence data; the parameters related to the main shocks’ focal mechanism and the main shocks’ parameters have a high contribution rate to the sequence classification, while the contribution rate of sequence parameters is extremely low. In overall, the results provided by the model are consistent with the actual empirical prediction methods. The above results can provide some ideas for the preliminary screening, exclusion, and selection of the complex and numerous feature parameters.

How to cite: Zhao, X., Su, Y., and Meng, L.: Research on the Importance of Feature Parameters in Seismic Sequence Type Determination Based on Decision Tree, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2853, https://doi.org/10.5194/egusphere-egu24-2853, 2024.

X1.74
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EGU24-2969
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SM1.1
Yih-Min Wu

Through the utilization of P-Alert network data from Taiwan, this study endeavors to estimate earthquake magnitude (Mcaa) using the cumulative absolute absement (CAA) methodology across varying window lengths after the arrival of P-wave. It is differentiated that even the proximity of the nearest 12 stations to the epicenter results in robust magnitude estimations. Notably, the standard deviation between the estimated Mcaa and the moment magnitude (Mw) using 12 stations decreases with the increase in window length and is found minimum for 5s window length. For 3s window the variation between Mcaa and Mw is found ±0.385, whereas, for 5s window it is ±0.313. Consequently, the estimation of Mcaa remains reliable. The magnitude Mpd is alternatively deduced from Pd, utilizing the closest 12 stations situated near the epicenter. The standard deviation of the order of ±0.412 is observed between the estimated Mpd and Mw for 3s window, whereas for 5s window it is ±0.281. A difference is observed using Mpdand Mcaafor comparison with Mw. The standard deviation error decreases for Mcaaand Mpd with increase in window length. While Mpd performs better under a 5s window scenario, it tends to underestimate the magnitude of an earthquake with a magnitude of Mw 7.0. On the other hand, CAA surpasses Pd in magnitude estimation, though with a slightly higher standard deviation compared to Mcaa. As a result, Mcaa is considered a more reliable magnitude indicator.

How to cite: Wu, Y.-M.: Cumulative absolute absement for magnitude determination in earthquake early warning system using low-cost sensors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2969, https://doi.org/10.5194/egusphere-egu24-2969, 2024.

X1.75
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EGU24-3321
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SM1.1
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ECS
Tuo Wang, Ling Chen, Stephen S. Gao, Kelly H. Liu, Youqiang Yu, Zhichao Yu, and Xu Wang

The Holocene Okavango Rift Zone (ORZ) marks the southern terminus of the Western Branch of the East African Rift System. Detailed knowledge of the crustal and lithospheric mantle structure of the ORZ is essential to decipher the rifting mechanism and nature of the lithosphere of this incipient continental rift. A 3-D shear wave velocity model from the surface to 160-km depth is constructed by jointly inverting the Rayleigh wave phase velocity dispersion and receiver function data through a non-linear Bayesian Monte-Carlo algorism. The crustal thickness estimates from our new velocity model generally agree with previous receiver function investigations of the region. The crust beneath the ORZ is thinned compared with the cratonic regions to both sides of the rift, suggesting a certain degree of continental stretching. Our velocity model also reveals two low velocity anomalies in the crust and upper mantle beneath the incipient rift, respectively. The shallow low velocity anomaly is mainly confined in the upper and middle crust, and the deeper low velocity anomaly extends from the Moho to at least 160 km depth, with a high-velocity lower crust (~4.0 km/s) in between. Although the two low velocity anomalies are probably both caused by rift-related decompression melting, the structural feature imaged suggests that they are generated separately and individually. Based on our observations, we propose that thermal upwelling and decompression partial melting in the upper mantle of the ORZ have a limited contribution to the stretching and thinning of the crust during the initiation of the continental rifting. The crustal rifting could be induced by an intra-plate relative motion between the South African block and the rest of the African continent along a pre-existing weak zone.

How to cite: Wang, T., Chen, L., Gao, S. S., Liu, K. H., Yu, Y., Yu, Z., and Wang, X.: Imaging of Crust and Lithospheric Mantle of the Incipient Okavango Rift Zone: Implications on the Rifting Mechanism, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3321, https://doi.org/10.5194/egusphere-egu24-3321, 2024.

X1.76
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EGU24-3496
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SM1.1
Youjin Su and Xiaoyan Zhao

 In the present study, seismic gaps are identified as periods with no occurrence of M ≥ 4.0 earthquake over dT ≥ 400 days. After examining all records in the Sichuan-Yunnan-Tibet-Qinghai junction area on the southeastern margin of the Tibetan Plateau in 1970−2022, a total of six M ≥ 4.0 seismic gaps were identified. Spatio-temporal images of the seismic gaps had similar characteristics and demonstrated spatial overlapping and statistical significance. The quiet periods of the six seismic gaps included 419−777 days (approximately 580 days on average). The semi-major-axis and semi-minor-axis lengths were in the 880−1050 km (approximately 987 km on average) and 500−570 km (about 533 km on average) ranges, respectively. Case analysis results revealed that the images of M ≥ 4.0 seismic gaps were of high significance in predicting M ≥ 6.7 strong earthquakes in the region, and they could be used as a predictive index on a time scale of about 1-0.5 year or less.

How to cite: Su, Y. and Zhao, X.: Characteristics and predictive significance of spatio-temporal space images of M ≥ 4.0 seismic gaps on the southeastern margin of the Tibetan Plateau, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3496, https://doi.org/10.5194/egusphere-egu24-3496, 2024.

X1.77
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EGU24-5100
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SM1.1
Marc Grunberg and Sophie Lambotte

In the continuation of the work carried out over the period 1962-2009 as part of the SI-Hex project, work is on going to revise the seismic catalog of mainland France from 2010 to 2018. This time period is characterized by both an upgrade of short-period stations with broadband stations and a major deployment of new broadband stations as part of the Résif-Epos research infrastructure (now called Epos-France), significantly increasing the amount of detected and processed events.

This catalog will benefit from our advances in the use of new artificial intelligence tools, such as PhaseNet, a deep learning automatic picking method, as well as in the development of a deep learning method for discrimination between earthquakes, quarry blasts and explosions.

This catalog will be built from those of the national observation service BCSF-Renass, CEA/LDG and regional seismological observatories (Isterre, OCA, OMP). The earthquake picks from these catalogs will be supplemented by those automatically obtained by deep learning on all the waveforms from the Epos-France (formerly Résif-Epos) stations daily used by BCSF-Renass (as part of its mission to monitor seismicity in mainland France) including stations from neighboring countries (GB, LU, BE, DE, CH, IT, ES), as well as those from temporary network stations (AlpArray, CifAlps2). 

The process workflow includes several steps. The first one consists in a clustering of picks close in time to reduce the amount of picks to process; duplicated picks are removed and priority is given to the manual ones. The second step is the association of seismic phases to create events, by combining the HDBSCAN algorithm - to merge picks close in time and space - with the PyOcto one - to discard picks that did not follow typical travel-time curves. The third step consists in event location using NonLinLoc algorithm with several regional models chosen based on the prior location obtained from PyOcto. At the last step, a moment magnitude Mw is computed (when possible) from waveform spectral fitting using a modified version of SourceSpec. To compute robust magnitudes in particular for low magnitude events, we include magnitude station corrections computed from statistics on magnitude differences between event and stations. Finally, events information (ie. origins, magnitudes) coming from the various catalogs are integrated into the multi-origin catalog according to the QuakeML standard, with the preferred location being the new one computed on the third step.

This catalog currently under revision will represent an update of seismicity in France over the period 2010-2018. Preliminary results show that it will incorporate a significantly increased number of low-magnitude events, detected thanks to the inclusion of picks from artificial intelligence tools. Event labeling is consolidated using our deep learning discrimination algorithm, and a Mw magnitude is calculated for each event using waveforms.

How to cite: Grunberg, M. and Lambotte, S.: A new workflow for revising the seismicity catalog for mainland France, covering the period 2010-2018, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5100, https://doi.org/10.5194/egusphere-egu24-5100, 2024.

X1.78
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EGU24-5890
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SM1.1
Hui-Chu Chen, Yuancheng Gung, Hsin-Yu Lee, and Li-Wei Chen

We report on the temporal variations of the near-surface (< 500 m) seismic structure (Vp, Vs, and Vs anisotropy) of Taiwan using the empirical Green’s functions of body waves between vertical station pairs at 60 borehole sites. In our previous work, the obtained near-surface anisotropy are categorized into stress-aligned anisotropy (SAA) and orogeny parallel anisotropy (OPA). Since all the major geological units of Taiwan are well sampled by borehole arrays, and drilling data for 52 sites are available, we were able to find that OPA is typically stronger than SAA, SAA strength is generally higher in sedimentary rocks, igneous rocks, and gravel sediments compared to fine-grained sediments, and OPA is more pronounced in foliated metamorphic rocks than in dipping sedimentary strata. In this study, we aim to address the following specific questions with the obtained results: (1) How do the temporal variations of near-surface seismic properties in different geological units of Taiwan correlate with seismic activity or nearby earthquake events? (2) Are there distinct patterns in the temporal variations of anisotropy strength based on the specific geological composition? (3) Do sites characterized by OPA exhibit different temporal variations in response to seismic activity compared to sites dominated by SAA?

How to cite: Chen, H.-C., Gung, Y., Lee, H.-Y., and Chen, L.-W.: On the temporal variations of near-surface seismic structure of Taiwan and its geological inferences, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5890, https://doi.org/10.5194/egusphere-egu24-5890, 2024.

X1.79
|
EGU24-6411
|
SM1.1
Yogesh Kumar

The Gorkha earthquake 25 April 2015 has attention the entire worlds to Himalaya due to large scale damage caused in the region. This heavy damage happened due to site amplification of the ground motion was clearly evident during the Nepal earthquake. The Himalaya situated in the central seismic gap (CSG) region suggested by Khattri (1987). Region itself has large possibilities of site amplification which can result high damage during future earthquakes. Average shear wave velocity up to 30 m depth are being described as Vs30. Correct estimates of Vs30 provides useful tool for site classification and site amplification at any location. This is important parameters for the engineering uses and is also used in seismic microzonation study of any area. In the present study Vs30 is measured in various locales of the Himalaya using the technique of multi-channel analysis of surface wave (MASW). Data has been acquired from the Sub-Himalaya to Lesser Himalaya for calculation of Vs30. Dispersion curves are obtained using the MASW data and are compared with the theoretical dispersion curve to obtain the shear wave velocity model at various point. Detail analysis of results obtained at various locations suggests that Vs30 in this region varies from 150 ms-1 to 900 ms-1.

How to cite: Kumar, Y.: Shallow Subsurface Velocity Structure using the ambient noise for the Himalaya Region., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6411, https://doi.org/10.5194/egusphere-egu24-6411, 2024.

X1.80
|
EGU24-7189
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SM1.1
|
ECS
Seula Jung, Dong-Hoon Sheen, Chang-Soo Cho, and Kwangsu Kim

The repeating earthquake (RE) ruptures a single fault patch repeatedly and generates highly similar waveforms. The RE is often observed in the area of subduction zones (Uchida and Matsuzawa, 2013; Yu et al., 2013; Uchida, 2019). However, even in the intraplate region, the RE has been found in the ruptured fault zones (Li et al., 2007; Li et al., 2011; Bisrat et al., 2012). We searched for REs around the epicenter of the 2008 ML 3.6 Gyerong earthquake that occurred in Mount Gyeryong, the Korean Peninsula, located in a stable intraplate region. In the study area, 48 earthquakes (ML 0.4–3.6) were reported during 2002–2022, while we found 50 earthquakes during 2018–2022 using a template matching. We located the events based on the Hypoellipse (Lahr, 1999), and also refined the hypocenters using the double difference method (hypoDD; Waldhauser and Ellsworth, 2000) to obtain the high-resolution fault geometry. It is found that the epicenters exhibit a linear alignment of the fault striking along WNW-ESE consistent with one of the strikes of the ML 3.6 event which has a strike-slip focal mechanism with a strike of 108° or 198°, a dip of 83° or 88°, and a rake of -2° or -173°, which indicates that the ML 3.6 earthquake occurred with a left-lateral fault slip. We estimated the rupture directivity of the ML 3.6 event from the apparent source time functions obtained by the empirical Green’s function approach. A vast number of microearthquakes including aftershocks of the ML 3.6 event occurred in the rupture direction (i.e. the east-southeast of the epicenter of the ML 3.6 event). We identified REs based on the waveform similarity (cross-correlation coefficient > 0.95) and their locations (co-location) to distinguish them from neighboring earthquakes. We found that the REs occurred within the rupture radius of the ML 3.6 event. Upon categorizing these REs according to their family duration, we identified three swarm-type families that occurred in 2007, 2009, and 2010, along with a continuous-type family spanning from 2011 to 2019. These observations demonstrate the close relationship between the REs and the ML 3.6, specifically highlighting the fault’s rupture and healing process.

How to cite: Jung, S., Sheen, D.-H., Cho, C.-S., and Kim, K.: Observation of intraplate repeating earthquakes within the fault zone of the 2008 ML 3.6 earthquake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7189, https://doi.org/10.5194/egusphere-egu24-7189, 2024.

X1.81
|
EGU24-12248
|
SM1.1
Michael Laporte, Michael Perlin, Marian Jusko, and David Easton

Earthquake early warning systems depend on the prompt, reliable arrival of seismic data at network data centers. Network operators invest significant resources into the design, installation and operation of real-time acquisition systems to ensure maximum data completeness and minimum data latency, to allow EEW processing modules to detect events and issue warnings as quickly as possible.

These mission-critical acquisition systems must perform before, during and after earthquakes, as main shocks are frequently preceded by foreshocks and followed by aftershocks, which are often just as dangerous. As such, a key consideration in the design of these systems is the impact that large earthquakes may have. Seismic data is generally encoded using Steim compression, which is a first difference algorithm. During large events the differences between samples grow, requiring more bits to record and, thus, increasing the data volume. This results in a surge in the throughput required during large events. System designers and network operators must be fully aware of this effect and plan for it accordingly.

This study expands on existing work to further characterize the impact of large events on seismic data compression and the corresponding spikes in throughput which must be supported by real-time acquisition systems. The study will examine the relationship between compression and various factors, including station magnitude, hypocentral distance, sample encoding technique, packet size, sample rate and system sensitivity.

How to cite: Laporte, M., Perlin, M., Jusko, M., and Easton, D.: Seismic Data Compression and Telemetry Bandwidth Considerations for Earthquake Early Warning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12248, https://doi.org/10.5194/egusphere-egu24-12248, 2024.

X1.82
|
EGU24-12588
|
SM1.1
Vincenzo Serlenga, Salvatore Lucente, Salvatore de Lorenzo, Edoardo Del Pezzo, Marilena Filippucci, Teresa Ninivaggi, Tony Alfredo Stabile, and Andrea Tallarico

High Agri Valley is an intermontane basin of the axial portion of Southern Apennines (Southern Italy), characterized by a very strong seismogenic potential. Indeed, a  Mw=7.0  earthquake occurred in 1857. Currently, the seismic networks managed by ENI Oil Company and INGV, installed in the area, continuously record a low-magnitude natural seismicity. Furthermore, two anthropogenic earthquake clusters are documented in two distinct sectors of the valley, located NE and SW of the artificial Pertusillo lake, respectively. The first cluster is related to the fluid-induced microseismic swarms caused by the injection, through the Costa Molina 2 well, of the wastewater produced by the exploitation of the Val d’Agri oilfield. The second cluster is due to a protracted reservoir induced seismicity (RIS) affected by the combined effects of the water table oscillations of the Pertusillo lake, the regional tectonics and likely the poroelastic/elastic stress due to aquifers in the carbonate rocks.

In this study we investigated the attenuation properties of the High Agri Valley crust by the estimation of the S-coda waves Qc-1, as it is widely recognized the role of fluids on this parameter. We selected a dataset of about 1800 events acquired from 2001 to 2015 by the two above mentioned seismic networks, with local magnitude (ML) ranging from 0 to 3.3. We estimated the attenuation of the target area by means of a linear regression analysis of the amplitude decay curves of the envelopes of the seismograms; these were filtered in the frequency ranges centered on 1, 2, 3, 4, 5, 6, 8, 10, 12, 14, 16 Hz. The Qc estimates were performed by using different time windows for the envelope fitting, starting from the time T1 to the time TL (the lapse time). In detail, we adopted, as T1, 1.0*Ts, 1.5*Ts and 2.0*Ts (being Ts the S wave arrival time), and as TL 10s, 15s, 20s, 25s and 30 s from the event origin time. Only the components for which the condition T1<TL<T2 was fulfilled were considered for the linear regression, being T2 the end-time of the coda envelope; the latter was automatedly found by a proper methodology implemented in this study.

The obtained results show the increase of Qc as a function of f at all the considered TL. Compared with other tectonic regions worldwide, in the High Agri valley the Qc(f) is very low: the Q0, that is the Qc at 1 Hz, ranges between 8 and 57. At greater frequencies, the highest estimated Qc value is lower than 400. These evidences could be interpreted as the effect of fluids in the investigated crust, thus providing a further hint on their possible role in the seismicity of the area. A complete characterization of seismic attenuation of the High Agri Valley will require further investigations, that is the separation of scattering and intrinsic contributions in the total attenuation and a 3D imaging: indeed, the latter could highlight possible overlapping between spatial attenuation anomalies and seismicity distribution in the investigated area.

How to cite: Serlenga, V., Lucente, S., de Lorenzo, S., Del Pezzo, E., Filippucci, M., Ninivaggi, T., Stabile, T. A., and Tallarico, A.: Preliminary estimation of attenuation properties in the High Agri Valley (Southern Apennines, Italy) by the coda attenuation method, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12588, https://doi.org/10.5194/egusphere-egu24-12588, 2024.

X1.83
|
EGU24-13440
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SM1.1
Satoshi Matsumoto

Size distribution of earthquakes, characterized by the power law decay (b-value), sometime displays the major earthquakes before their occurrence. The b-value reflect state of stress and proximity of fault failure condition according to previous studies. However, the causes are difficult to separate each other. This study proposes an additional indicator reflecting the proximity. Seismic moment release in a volume by small earthquake indicates inelastic strain. The efficiency of inelastic strain on stress loaded medium exhibits proximity to strength of the medium based on Mohr diagram and Coulomb failure condition. Thus, we adopt the efficiency as the indicator. We examine b-value and the efficiency variation in pre- and post- seismic activity of the 2016 Kumamoto earthquake sequence. Weighted b-value distribution by the efficiency captured the initiation point of the Kumamoto earthquake. The result suggests utilizing both b-value and the efficiency contribute to improving earthquake alerts and disaster mitigation.

How to cite: Matsumoto, S.: Inelastic strain efficiency of small earthquakes as an indicator for proximity of the 2016 Kumamoto earthquake (M7.3), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13440, https://doi.org/10.5194/egusphere-egu24-13440, 2024.

X1.84
|
EGU24-14903
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SM1.1
Takahiro Shiina, Haruo Horikawa, and Kazutoshi Imanishi

A large crustal earthquake (Mw=7.5) struck the Noto Peninsula, central Japan, at 16:10 (JST = UT + 9 hours) on New Year's Day, 2024. The main-shock rupture extended ~150 km in length, which covered the source regions of intense swarm activity in the northeastern tip of the peninsula [Amezawa et al., 2023] as well as the previous large crustal earthquakes such as the 2007 (Mw=6.7) and 2023 (Mw=6.3) events. The aftershock distribution of the 2024 event provides fundamental information for understanding the rapture process of the main shock and seismotectonics in the Noto peninsula. Therefore, we relocated the earthquake hypocenters that occurred immediately after the 2024 event by considering the three-dimensional velocity structure [Matsubara et al., 2022]. In the relocation, we applied the method proposed by Shiina and Kano [2022] to the arrival time data on the earthquake catalog compiled by the Japan Meteorological Agency. The applied method utilized the Markov Chain Monte Carlo technique, allowing us to evaluate uncertainty in hypocenter locations. Thus, we can discuss the distributions of the crustal earthquakes in and around the source area of the 2024 event, taking account of the spatial variations in uncertainty in the hypocenters. For example, some aftershocks occurred offshore, indicating that estimation accuracy in that area may get worse due to limited station coverage compared with the inland area. As the result of the relocation considering the three-dimensional structure, the depth of these offshore events was shifted about 5 km shallower. These hypocenters suggested that the aftershocks of the 2024 event occurred mainly between the ground surface and the depth of 15 km.

How to cite: Shiina, T., Horikawa, H., and Imanishi, K.: Relocations of earthquake hypocenters in and around the source area of the 2024 Mw 7.5 Noto Peninsula earthquake, Japan, by Bayesian inference, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14903, https://doi.org/10.5194/egusphere-egu24-14903, 2024.

X1.85
|
EGU24-15253
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SM1.1
|
ECS
Chin-Shang Ku, Bor-Shouh Huang, and Cheng-Horng Lin

In this study, we document unusual and recurring events that transpired within one hour on November 17, 2021. These incidents were identified through a seismometer array deployed in the Yilan area and Turtle Island, northeastern Taiwan. Preceding this series of events, a shallow submarine volcano near Turtle Island emitted sulfur smoke from October 28, 2021, lasting until November 22, 2021. This eruption was marked by a significant release of white sulfur smoke from the sea near Turtle Island. It reached a height exceeding 3 meters and extended over 100 meters into the air, making it the most substantial eruption of the year. At first, we proposed that the giant bubble could be generated during the submarine eruption and expanded through the water and into the atmosphere; the collapse of this bubble was considered a potential source of the recurring events. However, a grid-search method utilizing the arrival times of seismic stations indicates that the source location is close to the seacoast of Yilan, still dozens of kilometers away from Turtle Island. Upon further analysis of the seismic waveforms, it was observed that the propagation velocity is close to the speed of sound and only detected by surface stations, not by shallow-hole stations. This suggests that the source likely produced signals that couple well with the atmosphere rather than the solid Earth. The waveforms exhibit high consistency between different events at the same station, indicating that the sources occurred at the exact location several times within one hour. The possibility of an aircraft-induced shock wave was considered but needs more investigation. Trustworthy sources and their mechanisms remain to be clarified, and additional data, such as infrasound and pressure data, will be essential for a more comprehensive understanding shortly.

How to cite: Ku, C.-S., Huang, B.-S., and Lin, C.-H.: Repeating events detection in northeastern Taiwan using a broadband seismometer array, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15253, https://doi.org/10.5194/egusphere-egu24-15253, 2024.

X1.86
|
EGU24-15437
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SM1.1
Silvia Pondrelli

When in 1997 we started to compute Regional CMT for seismic events in the Euro-Mediterranean region, we could not expect to create a Catalog that can well describe the seismicity, the seismotectonics of this really active region with such complex characteristics. The RCMT Catalog includes more than 3200 seismic moment tensors for earthquakes with a magnitude starting from 4.5, but for the Italian region also down to M 4.0, for the time span 1997 to 2023. All RCMTs are available on the web, on dedicated pages, with the possibility to select the preferred dataset choosing intervals for time, geography, magnitude, depth and quality factors (http://rcmt2.bo.ingv.it/searchRCMT.html). In the first years the RCMT computation was based only on the modelling of intermediate-period surface waves. After 2002, it has been possible to invert also for body waves, an improvement that for the RCMT computation has been important for events with M greater than 5.0. The homogeneity of the dataset given by the continuous use of the same algorithm is an added value that has been underlined by several comparisons with other regional catalogs. The lower magnitude threshold applied in the Euro-Mediterranean region produces a dataset three times more numerous with respect to what is available with the Global CMT data only. In 1997 RCMTs were the only seismic moment tensors available for earthquakes with M lower than 5.0 in the Euro-Mediterranean region. Later, several regional and local focal mechanisms have been computed, with different methods and for different sub-regions. At present, on average three or more regional solutions appear on the web after a M4.5 earthquake hits the Mediterranean. However, RCMT Catalog is the one with the longer time interval covered by homogeneous data. Today, the Catalog is continuously updated with a few months of delay between definitive and quick solutions, that are however available on the RCMT web pages up to the time the revised solution is ready.

How to cite: Pondrelli, S.: The European Mediterranean RCMT Catalog: more than 25 years of activity and data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15437, https://doi.org/10.5194/egusphere-egu24-15437, 2024.

X1.87
|
EGU24-18530
|
SM1.1
Barbara Lolli, Paolo Gasperini, and Gianfranco Vannucci

We re-compute the coefficients of the intensity prediction equation (IPE) in Italy using the data of the DBMI15 V2.0 intensity database and the instrumental and combined (instrumental plus macroseismic) magnitudes reported by the CPTI15 V2.0 catalog. We follow the same procedure described in a previous article, consisting of a first step in which the attenuation of intensity I with respect to the distance D from macroseismic hypocenter is referred to the expected intensity at the epicenter IEand a second step in which IEis related to the instrumental magnitude Mi, the combined magnitude Mc, the epicentral intensity I0 and the maximum intensity Imax, using error-in-variable (EIV) regression methods. 

The main methodological difference with respect to the original article concerns the estimation of the uncertainty of IEto be used for EIV regressions, which is empirically derived from the standard deviation of regression between IE and Miand also used for the regressions of IEwith Mc, I0 and Imax. 

In summary, the new IPE determined from DBMI15 V2.0 is

                                        𝐼=𝐼𝐸−0.0081(𝐷−ℎ)−1.072[ln(𝐷)−ln(ℎ)]

 where 𝐷=√(𝑅2+ℎ2), h=4.49 km and IEcan be calculated from the intensity data distribution of the earthquake. If the intensity data distribution is not available, IEcan be calculated from the following relationships

                                        𝐼𝐸=−2.578+1.867𝑀𝑤

                                                      IE=I0

                                       

How to cite: Lolli, B., Gasperini, P., and Vannucci, G.: Recalibration of the intensity prediction equation in Italy using the Macroseismic Dataset DBMI15 V2.0, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18530, https://doi.org/10.5194/egusphere-egu24-18530, 2024.

X1.88
|
EGU24-18752
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SM1.1
|
ECS
Andrea Pio Ferreri, Annalisa Romeo, Rossella Giannuzzi, Gianpaolo Cecere, Salvatore de Lorenzo, Luigi Falco, Marilena Filippucci, Maddalena Michele, Giulio Selvaggi, and Andrea Tallarico

The OTRIONS seismic network (University of Bari Aldo Moro, 2013, FDSN code OT) is a local network installed in the Apulia region (Southern Italy) with the aim of monitoring the seismicity of the Gargano area (Northern Apulia) and the Salento area (Southern Apulia). OT network is managed by the University of Bari Aldo Moro (UniBa) and by the National Institute of Geophysics and Volcanology (INGV). It started to operate in 2013 and in 2019 the recording stations migrated to EIDA (all details can be found in Filippucci et al., 2021a). In 2021 a first database was collected, with the event detection achieved both manually and automatically with SeisComP3 (Helmholtz-Centre Potsdam), and was released (Filippucci et al., 2021a; Filippucci et al., 2021b).

Now, after ten years of operations, we focus on the microseismicity of the Gargano area with the aim of collecting a new seismic database for the period from April 2013 to December 2022, by using a recently acquired software, CASP (Complete Automatic Seismic Processor), for the automatic detection, picking and location of seismic events (Scafidi et al., 2019). The CASP software is installed on a remote server implemented by RECAS-Bari, the computational infrastructure of INFN and UniBa.

Through an appropriate parameter setting, we adapted CASP and NonLinLoc (Lomax et al., 2000) to the Gargano area and to the seismic stations available, both OT and INGV. We used the 1D velocity model of Gargano (de Lorenzo et al., 2017).

The recorded seismic events were organized in two catalogs: the first one is the automatic catalog, obtained from the automatic locations of CASP; the second one is the manual catalog, obtained through a manual revision of P and S waves arrival times. To evaluate the reliability of CASP, a comparison between the automatic and manual catalog was performed.

From a comparison of the manual catalog with the already released catalog of the Gargano seismicity (Filippucci et al., 2021b), the number of events detected by CASP increased a lot. Furthermore, the results show that the choice of the CASP parameters allows us to lower the minimum magnitude threshold of the recorded microseismicity in the Gargano area. Preliminary analysis of the earthquakes foci shows that the seismicity pattern retrace, substancially, the same discussed in the work of Miccolis et al., 2021.

How to cite: Ferreri, A. P., Romeo, A., Giannuzzi, R., Cecere, G., de Lorenzo, S., Falco, L., Filippucci, M., Michele, M., Selvaggi, G., and Tallarico, A.: The new earthquake catalog of the Gargano (Southern Italy) OTRIONS seismic network., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18752, https://doi.org/10.5194/egusphere-egu24-18752, 2024.

X1.89
|
EGU24-20889
|
SM1.1
Pierre Arroucau, Clara Duverger, Paola Traversa, Guillaume Daniel, Jessie Mayor, and Gilles Mazet-Roux

Modern ground motion prediction equations used in probabilistic seismic hazard assessment studies are now almost exclusively expressed as a function of moment magnitude MW. Yet, earthquake catalogues produced by seismic observatories often provide local magnitude ML only. It is for instance the case for the Laboratoire de Détection Géophysique (LDG) catalogue recently published by Duverger et al. (2021) for mainland France. A conversion relationship was proposed by Cara et al. (2015) from ML (LDG) to MW. It appears however that this relationship does not result in a good fit when compared to recently compiled MW values for France and neighboring areas (Laurendeau et al., 2020). In this work, we propose a new conversion relationship based on the inversion of ML-MW couples for events present in both the LDG catalogue and the compilation of Laurendeau et al. (2021). In order to avoid the choice of an arbitrary number of segments to model the MW=f(ML) relationship, the inverse problem is solved in a Bayesian framework by means of the reversible jump Markov chain Monte Carlo (rj-McMC) algorithm (Green, 1995; Bodin et al., 2012). The number of segments, as well as their respective slopes and intercepts, are jointly invert for. As moment magnitude uncertainty is not known, it is also considered as an unknown, while the ML uncertainties provided in the LDG catalogue are fully accounted for by random sampling during the McMC process. We observe a geographical dependence of the differences between the available MW values and those obtained from calculation so a location-dependent term is also modeled. This allows to account for the regional attenuation variations that can affect ML estimates. The new conversion law is then applied to the full LDG catalogue and its impact on seismic hazard assessment is explored.

How to cite: Arroucau, P., Duverger, C., Traversa, P., Daniel, G., Mayor, J., and Mazet-Roux, G.: Local to moment earthquake magnitude conversion in mainland France and implications for seismic hazard assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20889, https://doi.org/10.5194/egusphere-egu24-20889, 2024.