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General Contributions on Earthquakes, Earth Structure, Seismology

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.

Convener: Philippe Jousset | Co-conveners: Alice-Agnes GabrielECSECS, P. Martin Mai
| Tue, 24 May, 08:30–11:50 (CEST)
Room D3

Tue, 24 May, 08:30–10:00

Chairperson: Alice-Agnes Gabriel

Jannes Münchmeyer et al.

Seismic event detection and phase picking are the base of many seismological workflows. In recent years, several publications demonstrated that deep learning approaches significantly outperform classical approaches, achieving human-like performance under certain circumstances. However, as studies differ in the datasets and evaluation tasks, it is yet unclear how the different approaches compare to each other. Furthermore, there are no systematic studies about model performance in cross-domain scenarios, i.e., when applied to data with different characteristics.

Here, we present the results from a large-scale benchmark to address these questions. We compare six previously published deep learning models on eight datasets covering local to teleseismic distances and on three tasks: event detection, phase identification and onset time picking. Furthermore, we compare the results to a classical Baer-Kradolfer picker.

Overall, we observe the best performance for EQTransformer, GPD and PhaseNet, with a small advantage for EQTransformer on teleseismic data. Furthermore, we conduct a cross-domain study, analyzing model performance on datasets they were not trained on. We show that trained models can be transferred between regions with only mild performance degradation, but models trained on regional data do not transfer well to teleseismic data.

As deep learning for detection and picking is a rapidly evolving field, we ensured extensibility of our benchmark by building our code on standardized frameworks and making it openly accessible. This allows model developers to easily evaluate new models or performance on new datasets. Furthermore, we make all trained models available through the SeisBench framework, giving end-users an easy way to apply these models.


Published as Münchmeyer, J., Woollam, J., Tilmann, F., Rietbrock, A., Lange, D., Bornstein, T., Diehl, T., Giunchi, C., Haslinger, F., Jozinović, D., Michelini, A., Saul, J. & Soto, H. (2021). Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers. Journal of Geophysical Research: Solid Earth. doi.org/10.1029/2021JB023499

How to cite: Münchmeyer, J., Woollam, J., Rietbrock, A., Tilmann, F., Lange, D., Bornstein, T., Diehl, T., Giunchi, C., Haslinger, F., Jozinović, D., Michelini, A., Saul, J., and Soto, H.: Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4071, https://doi.org/10.5194/egusphere-egu22-4071, 2022.

Yijun Zhang et al.
Natalia Poiata et al.

Seismic activity in Romania is dominated by the intermediate-depth earthquakes generated inside the seismogenic body of the Vrancea seismic zone extending to the depth of 180 km. This earthquakes represent the main source of seismic hazard for Romania and neighbouring countries, with the most recent largest events of M 7.7 and 7.4 in 1940 and 1977 that caused significant and widespread destruction. Space distribution of the intermediate-depth earthquakes from Vrancea is constrained to a compact volume (60-180 km in depth and 20x50 km areal extent) falling into the category of, so called, “seismic nests”, which have peculiar and not well understood seismogenic mechanisms.

We present first results obtained by applying the automated waveform analysis schemes to the detection, location and characterization of seismicity from the Vrancea zone to the continuous data recorded at seismic stations of the Romanian seismic network. We evaluate the performance of the methods like network-based full-waveform coherency earthquake detection and location and the template-based waveform similarity analysis for building a detailed view of seismic activity in space and time and to provide a fully automated workflow for continuous seismic data analysis. We use case-specific, for Vrancea seismic region, synthetic example to test the detection and location scheme setup and resolution. The real dataset of continuous seismic data focuses on the two month time period around the recent, moderate (M 5.6) December 27, 2016 earthquake.

The preliminary results of the automated detection and location analysis indicate reduced foreshock and aftershock activity for this event. According to the Romanian earthquake catalog, this appears to be a common pattern for moderate (M ~5.0-6.0) magnitude events. We also discuss the results of the template-based waveform similarity analysis for the detected and located events, as well as how the combination of the two methods can contribute to the enhanced seismic monitoring and hazard assessment.

How to cite: Poiata, N., Grecu, B., Dinescu, R., Borleanu, F., and Tataru, D.: Investigating Vrancea intermediate depth seismic activity in Romania using automatic waveform processing methods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9062, https://doi.org/10.5194/egusphere-egu22-9062, 2022.

Marietta Csatlós and Bálint Süle

Local magnitude is one of the oldest and widely used term for characterizing the size of seismic events. Mostly based on the maximum amplitude measured on the components of the seismograms associated with the seismic event. The events in the Hungarian National Seismological Bulletin were relocated by Bondar et al. (2018). Before 2015 the bulletin did not contain amplitudes therefore it was not possible to calculate new local magnitudes for the new hypocenters. Moreover, the magnitudes were calculated by different methodology before 2015.

In this study, all three components of all available waveforms were collected for the events occurred between 1996 and 2016, and the local magnitudes were recalculated. Thus, we present a consistent data set for the whole period. Magnitude values based on both horizontal and vertical components are presented.

Amplitudes were measured on all three components, thus it was possible to compare the maximum amplitudes of the horizontal and vertical components recorded at stations in different geological conditions. For stations located on sediment, generally higher amplitude values were obtained on the horizontal components. The horizontal amplitude was 2.5 or 3 times larger for the Great Hungarian Plain stations on thick sediments. The differences between stations on firm bed rock were smaller.

The collected waveforms and amplitude measurements provide the opportunity to perform the calibration of the local magnitude scale to the geological conditions of Hungary.



Bondár, I., Mónus, P., Czanik, Cs., Kiszely, M., Gráczer, Z., Wéber, Z., the AlpArrayWorking Group. 2018: Relocation of Seismicity in the Pannonian Basin Using a Global 3D Velocity Model. Seismological Research Letters. pp.2284-2293.

How to cite: Csatlós, M. and Süle, B.: Recalculating the local magnitude of events in the Hungarian National Seismological Bulletin, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9192, https://doi.org/10.5194/egusphere-egu22-9192, 2022.

Felipe Vera et al.

Teleseismic back-projection has emerged as a widely-used tool for understanding the rupture histories of large earthquakes. However, its application often suffers from artifacts related to the receiver array geometry, notably the `swimming' artifact. We present a teleseismic back-projection method with multiple arrays and combined P and pP waveforms. The method is suitable for defining arrays ad-hoc in order to achieve a good azimuthal distribution for most earthquakes.

We present a catalog of short-period rupture histories (0.5-2.0 Hz) containing 54 events from 2010 to 2021 (Mw  7.5), including recent and significant earthquake ruptures, e.g., 2021 Mw 8.3 South of Sandwich Islands, 2021 Mw 8.2 Chignik, 2021 Mw 8.1 Kermadec Islands, and 2020 Mw 7.8 Simeonof Island.

The method provides semi-automatic estimates of rupture length, directivity, speed, and aspect ratio, which are related to the complexity of large ruptures. We determined short-period rupture length scaling relations that are in good agreement with previously published relations based on estimates of total slip. Rupture speeds were consistently in the sub-Rayleigh regime for thrust and normal earthquakes, whereas strike-slip events propagated in the unstable supershear range. Many of the rupture histories exhibited complex behaviors such as rupture on conjugate faults (e.g., 2018 Mw 7.9 Gulf of Alaska), bilateral ruptures (e.g., 2017 Mw 7.8 Komandorsky Islands), and dynamic triggering by a P wave (e.g., 2016 Mw 7.9 Solomon Islands). For megathrust earthquakes, ruptures encircling asperities were frequently observed, with down-dip (e.g., 2021 Mw 8.1 Kermadec Islands), up-dip (e.g., 2016 Mw 7.8 Pedernales), double encircling (e.g., 2015 Mw 8.3 Illapel), and segmented (e.g., 2020 Mw 7.8 Simeonof Island) patterns. Although there is a preference for short-period emissions to emanate from central and down-dip parts of the megathrust, emissions up-dip of the main asperities are more frequent than suggested by earlier results.

How to cite: Vera, F., Tilmann, F., and Saul, J.: A decade of short-period earthquake rupture histories from multi-array back-projection, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2839, https://doi.org/10.5194/egusphere-egu22-2839, 2022.

Andres Barajas et al.

Low-frequency seismic tremors and earthquakes play an important role in the understanding of the seismic processes occurring in seismogenic fault zones and volcanic systems. The covariance matrix, a method that analyses the spatial coherence of continuous seismic noise records on the surface, has proven to be an efficient tool to detect and localize seismovolcanic processes, allowing the classification between local earthquakes, tremors, and low-frequency earthquakes. We use this method in the analysis of tectonic seismic activity in the region of Shikoku, Japan, where a high rate of tremors and low-frequency earthquakes have been previously reported. The classification of the seismic activity over the spectral width and the network response function, shows distinct characteristic distributions from studies done in volcanic systems. We perform a series of synthetic tests that reproduce the classification patterns and spectral widths observed in volcanic and tectonic systems, allowing us to recognize fundamental differences in the duration, frequency and distribution patterns of volcanic and tectonic tremors and low-frequency earthquakes. 

How to cite: Barajas, A., Journeau, C., and Shapiro, N.: Covariance Matrix Analysis and Classification of Low-Frequency Tectonic Seismic Activity in Shikoku, Japan, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11974, https://doi.org/10.5194/egusphere-egu22-11974, 2022.

Janneke de Jong et al.

The receiver function method is widely used in seismology to study the characteristics of Earth’s major discontinuities. Ray theory and an assumed planar incoming wave are often used to estimate which regions of the mantle, crust and discontinuity contribute to the receiver function. To test the validity of these simplifying assumptions, we derived the adjoint source of a receiver function waveform misfit and applied the adjoint method on synthetic teleseismic receiver functions to calculate their sensitivity kernels of both subsurface velocity parameters in the mantle and boundary topography on the discontinuity. Here we focused on the P660s-phase and the 660-discontinuity. We observe a strong sensitivity to the wavefield far away from the discontinuity, particularly for the Vp sensitivity kernel. It has a strong sensitivity to the Fresnel zone of the P660s-phase before conversion, but also to the scatterers of the direct P-wave and other phases that arrive within the considered time window. This implies that mapping the observations solely to the P660s ray paths and ray-theoretical conversion points might be too simplistic and lead to inaccuracies in the conclusions. In general, a receiver function has a strong dependance on the background velocity models everywhere in the mantle. The boundary topography kernels have a sensitivity predominantly to the area near the conversion point. The diameter of the high-sensitivity area is roughly 300 km for an event with a source halftime of 5 s. Relatively weak sensitivity to the source region and the scatterers of the direct P-wave are observed in the boundary kernels as well. Our results show that using the adjoint method on receiver function waveforms to invert for mantle structure and boundary topography is possible and advisable. It allows for an automatic consideration of all contributing phases and scatterers arriving within the chosen time window, which is important for correctly dealing with velocity perturbations. The boundary kernels demonstrate that the receiver functions’ sensitivity to topography is concentrated to the region around the ray theoretical conversion point.

How to cite: de Jong, J., Paulssen, H., and Trampert, J.: Boundary and elastic parameter sensitivity kernels for a receiver function waveform misfit in a global earth., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8492, https://doi.org/10.5194/egusphere-egu22-8492, 2022.

Geoffrey Bainbridge et al.

Nanometrics new Trillium 360 GSN seismometer embodies the culmination of many years of research and technology innovation as well as extensive collaboration with and input from the scientific community interested in very broadband seismometry.  Several generations of seismometers with 240 or 360 second corner frequency have demonstrated successive improvements in self-noise at both very low and high frequencies.  The most recent development has produced the lowest self-noise of any vault seismometer, and is the only seismometer currently being manufactured that meets the performance requirements of a primary seismometer for the Global Seismographic Network and Geoscope. 

Posthole, Borehole and Vault form factors are available and being manufactured and delivered to the GSN.  Performance testing of several units of each model type has been carried out at the facilities of GSN participating member institutions.  The results of the performance testing are reviewed and interpreted, and compared with other co-located instrument types including the venerable STS-1.  Field deployment is now proceeding, to upgrade networks with the Trillium 360 GSN seismometer.  We will show results from new deployments as available at the time of the 2022 SSA conference.  

We will also present the Trillium 360 roadmap, with a smaller low-power version for ocean bottom and portable land deployments in development for 2022, and early test results as available.  The goal of this next phase is to bring very broadband performance to any location and environment at reduced logistical cost.

How to cite: Bainbridge, G., Townsend, B., Upadhyaya, S., and Hamilton, V.: Meeting the challenging performance requirements of Global Seismic Observatory Networks with the new Trillium 360 GSN, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10613, https://doi.org/10.5194/egusphere-egu22-10613, 2022.

Jessica Irving et al.

MERMAIDs (Mobile Earthquake Recording in Marine Areas by Independent Divers) are seismic instruments which record local, regional and teleseismic earthquakes, and other signals, in the oceans. In the Southern Pacific Ocean, some fifty MERMAIDs are collecting acoustic pressure time series as part of the South Pacific Plume Imaging and Modeling (SPPIM) project. Deployed in 2018 and 2019 by members of the EarthScope-Oceans consortium, these instruments record continuous time series data on a one-year buffer and autonomously report a wealth of waveforms, selectively triggered mostly by teleseismic events, suitable for mantle tomography. 

Listening for signals while roughly 1.5 km below the ocean surface, MERMAIDs' primary mission is to detect and deliver records of P-waves generated by distant earthquakes, and collectively they have returned many thousands of seismograms corresponding to such signals. We present highlights from our earthquake catalog and discuss the changing character and causes of the background noise. Whilst the South Pacific fleet is programmed to only send short seismic records, corresponding to confident identifications of teleseismic first arrivals, some records contain later-arriving phases. In addition to P-waves, we present a miscellany of observations of other signals, including core phases, converted S- and surface waves, and T-phases. Furthermore, we illustrate that we are able to obtain other recorded data segments through buffer requests via satellite. 

Data from the MERMAIDs owned by Geoazur and Princeton University that we report on here are being archived by IRIS—those from three instruments is available without embargo. We highlight MERMAID waveform availability and its utility to the scientific community via examples of their modeling and preliminary interpretations that can be made regarding wavespeed heterogeneity in the dynamic mantle below the Pacific Ocean. 

How to cite: Irving, J., Simon, J., Pipatprathanporn, S., Simons, F., and EarthScope-Oceans Consortium, T.: MERMAIDs in the South Pacific Ocean: Observations, Measurements, Modeling, Data Availability, and First Hints at Mantle Structure, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4238, https://doi.org/10.5194/egusphere-egu22-4238, 2022.

William Frazer and Jeffrey Park

Earth’s mantle transition zone (MTZ) is a possible global water reservoir and may be responsible for long-term (~100 Ma) ocean-mass regulation, driven by plate tectonics and mantle convection. Estimates of MTZ mineral water capacity exceed 1 wt%, far greater than that of rocks of either the upper- or lower-mantle. When water-rich material from the transition zone penetrates the upper or lower mantle, partial melting occurs due to the decrease in water capacity after phase transition, generating a reduction in seismic velocities. This process can add an additional low-velocity zone (LVZ) that can be imaged above(below) the 410(660)-km discontinuities, if melt is present. Depending on the melt fraction and wetting angle at mineral-grain boundaries, decreases in shear velocity of 0.5-2.6% can be generated. Seismic receiver functions have detected velocity reductions both above and below the MTZ, interpreted to be partial melting induced by high water content under the Alpine orogeny, in the deep Japan-slab subduction zone, and across the western United States. Since much of Earth lacks seismic stations, we apply SS precursors to conduct a global survey for such LVZs. The precursors to the SS phase reflect off interfaces near the source-receiver midpoint, so seismic stations are not required to be located above the target region. Detection and interpretation of LVZs surrounding sharp positive-velocity gradients, such as the 410- or 660-km discontinuity, is often complicated by side lobes, an artifact of common signal-processing routines. To address this challenge, we develop an SS precursor method based on the multitaper-correlation (MTC) technique. MTC allows for analysis at higher frequency, leading to finer depth resolution, and can increase the number of useful data records. We conduct MTC SS-precursor analysis for seismic waveforms recorded on the ~125 stations of the Global Seismographic Network to benchmark our new method and search for LVZs. Results will be compared to LVZs interpreted from previous seismic analysis.

How to cite: Frazer, W. and Park, J.: Searching for Mid-Mantle Water with Multitaper-Correlation SS Precursors, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8833, https://doi.org/10.5194/egusphere-egu22-8833, 2022.

Ayoub Kaviani et al.

We use seismological data collected from a recently deployed seismic network around the Klyuchevskoy Volcanic Group (KVG) in Kamchatka to study the crustal structure and mantle anisotropy beneath the region. In order to improve and extend the data coverage, we combined this data set with data from previous temporary deployments and permanent stations to reach a total number of 145 stations covering a region defined in the geographic coordinates 150°-167°E and 50°-61°N.

We use receiver function (RF) analysis to study the crustal structure beneath the study area. P-RFs are migrated to depth and stacked to image seismic interfaces beneath the network of seismic stations. We used a recently published three-D seismic tomography model to migrate the RFs from time to space domain. The RF amplitudes are stacked in the space domain using the Common Conversion Point (CCP) approach. The stacked RF amplitudes provide a 3-D image of seismic interfaces. The use of the 3-D velocity model helps migrate the RF amplitude to correct depths so that the depth and geometry of subsurface interfaces are constrained more correctly.  Furthermore, we are able to better compare the 3-D CCP images with the 3-D tomography model. In addition, at stations with a sufficient number of RFs, we also tried to calculate Moho depth and mean Vp/Vs ratio using the single-station H-k stacking approach. This analysis provides a way to better identify the interfaces beneath different locations and verify and adjust the depths obtained using the CCP stacking. We found a relatively complex crustal structure in the entire region of the KVG that laterally merges to a simpler structure to the west. Seismic tomography images provide better lateral resolution of velocity anomalies while RF analysis provides better vertical resolution of vertical velocity constants. Our RF-CCP images reveal two main interfaces beneath the active volcanic region. The shallow interfaces with a limited lateral extent have depths varying between 20 and 30 km. The deeper interface occurs at depths 50-60 km with an east-to-west dipping direction. In comparison with the seismic tomography model, we infer that the shallow interface is related to a velocity increase from <6 km/s to >7 km/s, implying the presence of a shallow low-velocity zone beneath the volcanic group. The deeper interface that correlates with a velocity increase from <7 km/s to around 8 km/s might be related to the top of the subducting plate. 

In addition to the RF analysis for the crustal structure, we also perform splitting analysis of core-refracted shear waves (SKS) to study mantle seismic anisotropy as a proxy for the pattern of the mantle flow field. Our SKS-splitting analysis indicates a trench-normal mantle flow beneath the eastern edge of the Kamchatka peninsula that converts to a more complex pattern beneath the KVG region. We argue that this pattern of fast polarization direction suggests the rotational mantle flow that may be related to a slab gap at the junction between the Kuril-Kamchatka and Aleutian arcs.

How to cite: Kaviani, A., Rümpker, G., Koulakov, I., Sens‐Schönfelder, C., and Shapiro, N.: Crustal structure and mantle anisotropy beneath Klyuchevskoy Volcano and surrounding regions in Kamchatka, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2498, https://doi.org/10.5194/egusphere-egu22-2498, 2022.


Tue, 24 May, 10:20–11:50

Chairperson: Alice-Agnes Gabriel

Abolfazl komeazi et al.

We perform an adjoint waveform tomography using Rayleigh-wave empirical Green‘s functions (EGFs) at periods 10-50 s to improve a pre-existing 3-D velocity model of the crust and uppermost mantle beneath the Iranian plateau. The starting model was derived from a conventional surface-wave dispersion tomography based on high-frequency ray-theory assumption to invert of a quasi-3-D shear-wave velocity model. We use the EGFs from the same study that were derived from cross correlation of continuous seismic noise. Adjoint tomography refines the initial model by iteratively minimizing the frequency-dependent travel-time misfits between synthetic and observed EGFs measured in different period bands. Our new model covers the known tectonic units such as the Central Iranian Block, Zagros fold-and-thrust belt, Sanandaj-Sirjan metamorphic zone and Urumieh-Dokhtar magmatic arc.

Overall, the adjoint tomography provides images with better lateral resolution and depth sensitivity and more realistic absolute velocity values due to the inclusion of finite-frequency waveforms. The use the numerical spectral-element solver in adjoint tomography provides accurate structural sensitivity kernels, which helps to obtain more robust images rather than those generated by ray-theory tomography. The final model adjusts the shapes of velocity anomalies at crustal depth more specifically for the eastern Zagros. The final model significantly improves the initial model at the upper mantle depths and provides a higher resolution for the shape of velocity anomalies.

How to cite: komeazi, A., Kaviani, A., Yaminifard, F., and Rümpker, G.: An Improved shear velocity model beneath the Iranian plateau using adjoint noise tomography, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3017, https://doi.org/10.5194/egusphere-egu22-3017, 2022.

Julien Barrière and Adrien Oth

The Eifel region is a large volcanic system in the middle of European continent. From the Eifel teleseismic tomography experiment (8 months in 1997-1998), a mantle plume beneath the volcanic fields (down to 400 km depth) has been identified and further confirmed by receiver function and teleseismic surface wave dispersion analyses. A study in 2020 using dense geodetic observations leads to the conclusion that the Eifel region experiences a pronounced uplift encompassing the neighbouring countries Netherlands, Belgium, Luxembourg and France, which is attributed to the same buoyant mantle plume.

A detailed focus on the uppermost 30 km above the Moho has been missing until recently. However, a noteworthy recent seismological investigation showed the evidence of a deep magmatic recharge beneath the Laacher See Volcano in East Eifel between 2013 and 2018. Located at depth roughly between 40 and 10 km, low-frequency seismic swarms, which are typical of volcanic environment, convey the presence of magma movements and potential storage zones in the crust.  

The present study aims to bring additional information on this shallow active magmatic system using an Ambient Noise Tomography (ANT). Thanks to theoretical and technical developments over the two last decades, this approach has been increasingly popular for imaging Earth structure worldwide at different scales. We use here ambient noise data from archives of the 1997-1998 Eifel experiment and more recent (2019-2020) continuous seismic record. The group velocity dispersion of Rayleigh waves are estimated between station pairs from Noise Cross-correlation Functions (NCF) covering the secondary microseismic frequency band, which allows to sample the uppermost 10-20 km of the crust. Our contribution includes a complete description of the ANT/NCF processing (e.g., directivity of the noise sources, sensitivity tests) in order to better constrain the velocity anomalies observed in the Eifel region and around.

How to cite: Barrière, J. and Oth, A.: Imaging the uppermost layers of the Eifel volcanic system (Germany) using ambient microseismic noise, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7268, https://doi.org/10.5194/egusphere-egu22-7268, 2022.

Hamzeh Mohammadigheymasi et al.

A large volume of digital seismic data was recorded by six broadband seismic sensors equipped with GPS-clock timing in the Ghana Digital Seismic Network (GHDSN) between October 2012 and April 2014. For this period, no public seismicity catalog was reported by the global data centers, International Seismological Center (ISC), and United States Geological Survey (USGS) for southern Ghana. In this study, this database is processed to detect local earthquakes. To facilitate the challenging and time-consuming process of detecting the earthquakes and picking the arrival times of P and S phases, we utilize EQTransformer, a Deep Learning (DL) model deploying Hierarchical Attention Mechanism (HAM) for simultaneous earthquake detection and phase picking. This model utilizes global and local levels of attention mechanism for identifying earthquake and seismic phases deriving benefits from deep neural networks, including convolutional and recurrent neurons. The thresholding values of 0.2, 0.07, and 0.07 are set for earthquake detection, P-picking, and S-picking, respectively. As a result, a list of events for each station of the network with the associated time of detection, as well as P and S phase arrivals are obtained. Taking these arrival times into account, we have devised a so-called ”conservative strategy” to optimally extract all possible earthquakes in the data set, amenable to locate. Initially, a list of preliminary events recorded by at least two stations is created by comparing the earthquake occurrence and arrival times of the P and S phases for all stations regarding a 100 sec time threshold. The list in this step includes 317 events recorded by at least two stations. Eventually, an analyst controls the obtained waveforms in other stations assesses whether EQTranasformer misses the preliminary list of events in those stations. Consequently, a number of 533 picked phases (282 P and 251 S) recorded by a minimum of 3 stations are finalized. Incorporating these phases and removing the instrument response from the waveforms, the hypocentral parameters for 73 earthquakes with 2.5 ≤ M L ≤ 4.0 are estimated. The main concentration of events is on the intersection of the Akwapim fault zone and the coastal boundary fault, with some scattered seismicity along the Akwapim fault zone. The corresponding set of seismic phases is utilized to estimate an updated 1D crustal velocity model for the study area. This research contributes to the FCT-funded projects SHAZAM (Ref. PTDC/CTA-GEO/31475/2017), RESTLESS (Ref. PTDC/CTA-GEF/6674/2020), SIGHT (Ref. PTDC/CTA-GEF/30264/2017), and IDL (Ref. UIDB/50019/2020).

How to cite: Mohammadigheymasi, H., Tavakolizadeh, N., Mousavi, S. M., Silveira, G., and Fernandes, R.: Seismicity analysis in southern Ghana- I: Detecting local earthquakes by Deep Learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5860, https://doi.org/10.5194/egusphere-egu22-5860, 2022.

Susana Custódio et al.

A small network of six broadband seismic sensors operated in southern Ghana between October 2012 and April 2014 (GHDSN). During this period, no seismicity was reported by the global data centers, however application of the Deep Learning algorithm EQTransformer resulted in the detection and subsequent location of 73 earthquakes. Preliminary constant crustal velocity models with  vp=5.55 km/s and vs=3.36 km/s have been utilized since 2002 to locate the local earthquakes in southern Ghana. Using this crude velocity model resulted in scattered seismicity, hinting into a likely inadequacy of these preliminary velocity parameters to represent the elastic properties of the area. In this study, we perform a joint-inversion for estimating an updated 1D crustal velocity model and the hypocentral parameters of the 73 recently detected local earthquakes. A grid search method is implemented and a 6-layer velocity model is defined, down to 45 km crustal depth. The space of velocity model parameters is searched by altering the upper depth of the layers (ud), P-wave velocity in each layer (vp), and the ratio of vp/vs. The optimized velocity model and hypocenteral parameters are evaluated by minimizing the RMS error function between the observed (533 picked phases consisting of 282 P and 251 S phases) and calculated arrival times. A two-step implementation is devised to increase the computational efficiency of the inversion process. Initially, the optimum  vp/vs is estimated by implementing a coarse grid search on vp and ud values. Then, incorporating the optimum vp/vs a fine grid search on vp and ud is applied.
The results yields layers with 1, 13, 8, 13 and 10 km thickness, with vp = 5.9, 6.1, 6.3, 6.5, 6.9 and 7.2 km/s, respectively. The updated velocities for the first and last layers are 6% and 26% percent higher than the previously reported constant velocity models. Furthermore, the updated vp/vs=1.70 is 0.03% higher than the corresponding value vp/vs=1.65 of the constant velocity model. The updated hypocentral locations of the 73 earthquakes with  2.5<ML<3.9 are concentrated on five major clusters. Two clusters are located on the AFZ, indicative of the active role of this structure in the seismicity of the region. Two other clusters, which have the highest rate of activity,  are positioned in the intersection between the AFZ and CBF. The last cluster consists of scattered earthquakes that coincide with mapped segments of the AFZ. Incorporating the updated velocity model for estimating the hypocentral parameters resulted in enhanced seismogenic source delineation in southern Ghana.  This research contributes to the FCT-funded projects SHAZAM (PTDC/CTA-GEO/31475/2017), RESTLESS (PTDC/CTA-GEF/6674/2020), SIGHT (PTDC/CTA-
GEF/30264/2017) and IDL (UIDB/50019/2020).

How to cite: Custódio, S., Mohammadigheymasi, H., Tavakolizadeh, N., Matias, L., and Silveira, G.: Seismicity analysis of Southern Ghana II: Updated crustal velocity model and hypocentral parameters, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5570, https://doi.org/10.5194/egusphere-egu22-5570, 2022.

María del Puy Papí Isaba et al.

We present a preliminary analysis of two seismic sequences between March and April 2021, near Neunkirchen and Gloggnitz, about 50 km from Vienna, Austria, and around 15 km apart from each other. Despite the moderate magnitudes, the recent earthquakes in the epicentral region, in the southern part of the Vienna Basin, were felt in the epicentral region and up to a distance of 300 km away. 

The Neunkirchen sequence started on March 11th, 2021. According to the Austrian Seismological Service at ZAMG, the last recorded earthquake occurred on May 12th, 2021. Over 245 earthquakes, with local magnitudes ranging from 0.5 to 4.6, were recorded until mid of May 2021. Out of the 245 earthquakes, 21 were felt by the population (1.8 ≤ ML ≤ 4.6), and two of them (ML4.6 and ML4.4) caused minor damage in the epicentral region. According to the Austrian Seismological Service, the depths of this sequence ranged from 7 to 12 km. 

The Gloggnitz sequence started on April 1st, 2021, and continued until May 8th, 2021. The epicenters of 65 detected earthquakes were located. Four earthquakes were felt, from which two (ML3.6 on April 20th and ML3.8 on April 23rd) caused slight damage. The local magnitudes of this seismic sequence ranged from -0.3 to 3.8; depths varied between 4 and 7 km. 

The relocation of the earthquakes of both sequences was carried out using the NonLinLoc by Lomax et al. (2019). We obtained the ellipse error for all relocated earthquakes. The focal mechanisms of the largest earthquakes were calculated using Seismic Moment-Tensor-Inversion. For the remaining events, a joint fault-plane solution was investigated. Furthermore, we compiled and analyzed the macro-seismic questionnaires of all felt earthquakes in the series and produced intensity maps (EMS-98). We compared the intensity attenuation as a function of distance with the newly available data and derived an Intensity Prediction Equation (IPE) for the region.

How to cite: Papí Isaba, M. P., Lenhardt, W., Meurers, R., Apoloner, M. T., Hausmann, H., Mattesini, M., and Buforn, E.: Preliminary results of the two seismic sequences in the Vienna Basin in March and April 2021 , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11076, https://doi.org/10.5194/egusphere-egu22-11076, 2022.

Pierre Arroucau et al.

Seismic event locations are usually performed by means of iterative, linearized arrival time inversion considering 1D velocity models with fixed data errors. Both the use of inaccurate velocity structure or data error estimates may however affect the quality of event location and uncertainty evaluation. Here, we test a 3D P- and S-wave velocity model built in a previous work for Metropolitan France (the part of France located in Europe) and we compare it with the “Auvergne” 1D velocity model used by BCSF-RéNaSS (Bureau Central Sismologique Français - Réseau National de Surveillance Sismique) using quarry blast data. The reason for using quarry blast data is that, to some extent, their epicentral location and depth are known, which is not the case for earthquakes. We first identify potential active quarries over the territory of Metropolitan France by comparing catalog quarry blast locations with those from quarries visible from satellite images. Relocation is achieved by means of a Hierarchical Bayesian inversion procedure in which not only the hypocentral parameters (longitude, latitude, depth, origin time) are inverted for, but also P- and S-wave arrival time errors. The area of interest is a 1° by 1° zone located between 4°E and 5°E in longitude and 44°N and 45°N in latitude, the region where the Le Teil earthquake occurred (Mw 4.9, 2019/11/11). We first demonstrate the ability of the algorithm to properly determine hypocentral parameters and data noise using two simple synthetic experiments. Then we apply it to real data and relocate 147 quarry blasts that occurred in the region between 1980 and 2020 and that were located wit the “Auvergne” 1D velocity model. Relocations obtained with the 1D and 3D model are rather similar. Estimated data errors are larger, in both cases, than the amplitude of picking uncertainties, meaning that both models could be improved, by seismic arrival time tomography for instance. They are larger in the 3D case, suggesting that, from that point of view, the 1D model is in better agreement with the data. Distances between relocated hypocenters and the closest known quarry are comparable but relocations with the 3D model are characterized by shallower hypocenters than those obtained with the 1D model, so they appear more consistent with the fact that events are quarry blasts. In both cases, some events are quite far away from the closest quarry, suggesting that some of them might be natural events.

How to cite: Arroucau, P., Mayor, J., Grunberg, M., Nayman, E., and Daniel, G.: Testing seismic velocity models with quarry blast data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8652, https://doi.org/10.5194/egusphere-egu22-8652, 2022.

Retno Agung Prasetyo et al.

A major earthquakes struck the Majene Regency, in West Sulawesi province, Indonesia, on 15 January 2021 at 02.28 local time, the hypocenter is 2.97°S, 118.99°E, depth 38.0 km, with moment magnitude Mw 6.2 with an epicenter located about 6 km Northeast Majene, West Sulawesi. This large event causing extensive damage, great economic loss and casualties in the Majene city and surrounding region. The mainshock preceded by significant foreshock on 14 January 2021 at 14.35 local time, 3°S, 118.94°E, depth 10.0 km Mw 5.9, epicenter was located at about 4 km Northwest of Majene. The faulting orientation of the mainshock, and foreshock was strike = 330°, dip = 17°, and slip = 59°, and strike = 353°, dip = 29°, and slip = 61°, respectively, is possibly related to Mamuju-Majene thrust fault. Focal mechanism solutions for the earthquakes indicate rupture occurred thrust fault with low dip angle. The mainshock was followed by low aftershocks productivity may due to homogeneous faulting systems and relatively uniform stress state in that region. We use hypocenter relocation, stress drop, coulomb stress and seismic hazard (PSHA) to investigate the earthquake characteristics and seismic hazard analysis. The distribution of hypocenter relocations indicate aftershock ruptured northern extension of the mainshock. This result supports that the highest of acceleration is the north component of the three component recorded acceleration, this detect the components of directivity toward the north for the foreshock distribution.

How to cite: Prasetyo, R. A., Rohadi, S., Yuliatmoko, R. S., Rahman, A., Perdana, Y. H., Riama, N. F., Adi, S. P., Karnawati, D., and Prayitno, B. S.: Characteristic of Source and Seismic Hazard Analysis of Majene Earthquake Mw 6.2, January 15, 2021, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8496, https://doi.org/10.5194/egusphere-egu22-8496, 2022.

Supriyanto Rohadi et al.

A major earthquakes struck the north of Flores island, in Nusa Tenggara Timur, Indonesia, on 14  December 2021 at 10:20:22 local time, the hypocenter is 7.59°S, 122.26°E, depth 12.0 km, with moment magnitude Mw 7.4. The faulting orientation of the mainshock, fault plane was strike = 290°, dip = 89°, and rake = 177°, and the auxiliary plane was strike = 21°, dip = 87°, and rake = 1°, respectively, is possibly related to thrust fault in the sea. Focal mechanism solutions for the earthquakes indicate rupture occurred thrust fault with large dip angle. The mainshock was followed by low aftershocks productivity may due to homogeneous faulting systems and relatively uniform stress state in that region. We analyze aftershock hypocenter relocation and gravity anomaly, slip distribution, coulomb stress and seismic hazard (PSHA) to investigate the earthquake characteristics and seismic hazard analysis. The distribution of hypocenter relocations show that aftershock ruptured distribute between two block of high gravity anomaly, its indicate that it was not the new fault. The inversion of the source model shows several time periods of energy release with three main peaks. These temporal rupture suggest repetition of a large scale slip on the large asperity. The models of coulomb stress indicate that static stress transfer due to the Mw 7.4 earthquake is suitable with aftershock spatial distribution. We compute the probabilistic seismic hazard assessment in the Flores region for Earthquake mitigation

How to cite: Rohadi, S., Prakoso, T. A., Yatimantoro, T., Rahman, A., Sunardi, B., Adimarta, A., Riama, N. F., Adi, S. P., Adi Wibowo, B., and Karnawati, D.: The 14 December 2021, Mw 7.4 Flores Earthquake: Review of the hypocenter relocation, slip distribution, coulomb stress, and seismic hazard, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8366, https://doi.org/10.5194/egusphere-egu22-8366, 2022.

Pepen Supendi et al.

On December 14, 2021, the Mw 7.3 Flores Sea earthquake occurred approximately 100 km to the north of Flores Island, one of the most complex tectonic settings in Indonesia. The existence of the causative fault that generated this earthquake was not been previously known, therefore making further analysis crucial for assessing future seismic hazard in the region. In this study, we relocated the hypocenter of the mainshock and aftershocks using a double-difference method, determine focal mechanisms using waveform inversion, and then analyse stress changes to estimate the fault type and stress transfer caused by this earthquake. Our relocated hypocenters show that this earthquake sequence ruptured on at least three segments: the source mechanism of the mainshock exhibits dextral strike-slip motion (strike N288oW and dip 78o) that occurred on a West-East trending fault which we call the Kalaotoa Fault, while rupture of the other two segments located to the west and east of the mainshock (WSW-ESE directions, respectively) may have been triggered by this earthquake. The Coulomb stress change of the mainshock shows that areas to the northwest and southeast experienced an increase in stress, which is consistent with the observed aftershock pattern.

How to cite: Supendi, P., Rawlinson, N., Prayitno, B. S., Widiyantoro, S., Palgunadi, K. H., Simanjuntak, A., Kurniawan, A., Marliyani, G. I., Nugraha, A. D., Daryono, D., Fatchurochman, I., Sadly, M., Adi, S. P., Karnawati, D., Gunawan, M. T., and Arimuko, A.: Preliminary results of investigation of “unidentified fault” associated with the Mw 7.3 Flores Sea earthquake, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3794, https://doi.org/10.5194/egusphere-egu22-3794, 2022.

Matteo Picozzi et al.

Near-fault observations can provide insights into the physical process interaction between fault slip activation, fluid presence/migration and seismicity production, processes acting at different timescales that generate large earthquakes.

The DETECT experiment aims at exploiting very dense seismic networks deployed across a segmented faults system to foster the development of scientific integrated methodologies for monitoring and imaging the faults behavior during the inter-seismic phase. Target of the monitoring is to: detect and track space-time trends of different source parameters that could be related to a preparation process leading to a larger earthquake; investigate the frictional and stress states of the fault segments to anticipate the characteristics of the future large earthquake (e.g., hypocenter but also future large seismic energy release locations); analyze the interactions between the different fault segments to model/anticipate potential cascade effects.

The DETECT experiment is carried out in the Irpinia area (southern Italy), one of the regions in Italy and Europe showing the highest seismic hazard. Since august 2021, a constellation of 20 seismic arrays, for a total of 200 seismic stations (20 broad-band sensors and 180 short-periods), has been installed over the fault segments responsible for the Ms 6.9, 1980 Irpinia earthquake, the strongest and most destructive seismic event of the last half-century in southern Italy.

DETECT results from a joint effort of local Universities, National and International Research Institutes. A novel and crucial aspect is that, differently from most studies concerning intra-plate earthquakes which are usually carried out after that large magnitude earthquakes have occurred, DETECT aims to put us in advantageous position and to unveil the preparatory process that generate large earthquakes and anticipate the role of the segmentation by studying at one time different fault segments, some of which are in rather late stage of their seismic cycle.

With this contribution, we aim to present the DETECT experiment, the preliminary results and foster additional cooperation including complementary expertise to further enrich the partnership.

How to cite: Picozzi, M., Iaccarino, A. G., Bindi, D., Cotton, F., Festa, G., Strollo, A., Zollo, A., Stabile, T. A., Adinolfi, G. M., Martino, C., Amoroso, O., De Matteis, R., Convertito, V., and Spallarossa, D. and the DETECT team: The DEnse mulTi-paramEtriC observations and 4D high resoluTion imaging (DETECT) experiment, a new paradigm for near-fault observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8536, https://doi.org/10.5194/egusphere-egu22-8536, 2022.

Spyridon Mavroulis et al.

On September 27, 2021, an Mw=6.0 earthquake struck the central part of Crete Island (southern Greece) and in particular the Heraklion Region. This event was preceded by an extended foreshock sequence started on early July 2021 and it was followed by an Mw=5.3 aftershock on the following day.

Taking into account the spatial distribution of foreshocks and aftershocks and the focal mechanism of mainshock as well as the active faults of the earthquake-affected area, it is evident that the seismic activity is strongly related to the NNE-SSW striking W-dipping faults of the Kasteli fault zone located along the eastern margin of the Neogene to Quaternary Heraklion Basin. The latter has been filled with Miocene to Holocene post-alpine deposits.

A field reconnaissance conducted by the authors in the earthquake-affected area shortly after the mainshock revealed that the earthquake-triggered effects comprised mainly rockfalls and slides, as well as ground cracks within or close to landslide zones. These effects were located within the hanging-wall of the KFZ. The affected sites are mainly composed of Miocene deposits and they are characterized by pre-existing instability conditions and high susceptibility to landslides. Far field effects were also observed south of the earthquake-affected area and in particular in the southern coastal part of Heraklion Region.

In regards to the spatial distribution of the earthquake-induced building damage, the vast majority was caused in villages and towns founded on Miocene and Holocene deposits of the hanging-wall. Damage was not reported in settlements located in the footwall, which is composed of alpine formations.

The dominant building types of the earthquake-affected area comprise: (i) buildings with load-bearing masonry walls made of stones and bricks with clay or lime mortar, mainly constructed without any anti-seismic provisions and (ii) buildings with reinforced-concrete frame and infill walls constructed according to the applicable seismic codes. The former suffered the most severe structural damage including partial or total collapse in many villages founded on post-alpine deposits of the hanging-wall of KFZ. The latter responded satisfactory during the mainshock and were less affected with only non-structural damage including cracking, detachment of infill walls from the surrounding reinforced concrete frame, peeling of concrete and short-column failures.

From the abovementioned, it is concluded that the impact of the 2021 Arkalochori earthquake was limited to the hanging-wall of the causative fault zone and in particular to residential areas founded on post-alpine deposits and to slopes highly susceptible to failure within the Heraklion Basin.

How to cite: Mavroulis, S., Kranis, H., Lozios, S., Argyropoulos, I., Vassilakis, E., Soukis, K., Skourtsos, E., Lekkas, E., and Carydis, P.: The impact of the September 27, 2021, Mw=6.0 Arkalochori (Central Crete, Greece) earthquake on the natural environment and the building stock, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7994, https://doi.org/10.5194/egusphere-egu22-7994, 2022.

Michael Whitworth et al.

Post-earthquake reconnaissance missions are critical to understand the event characteristics, identify building and infrastructure vulnerabilities, and improve future construction practice. However, in-field missions can present logistic and safety challenges that do not make them viable in every post-disaster scenario. Remote sensing technique can be used to rapidly collect a large amount information that can be used to enrich the post-event learning process. While the possibility to deploy teams in the field remain a valuable asset for an integrated understanding of technical and socio-economic factors, a mix of remote and in-field reconnaissance activities can be a way forward in post-disaster management.

This work presents the results of a hybrid mission mobilised by the Earthquake Engineering Field Investigation Team (EEFIT) after the 2021 Haiti earthquake. On 14 August 2021, a 7.2 magnitude earthquake struck the Tiburon Peninsula in the Caribbean nation of Haiti, approximately 150km east of the capital Port au Prince. The event was followed by numerous aftershocks up to magnitude 5.7, and tiggered over 1000 landslides. Over 2000 people lost their lives, with over 15,000 injured and over 137,000 houses damaged or destroyed. The estimated economic impact is of the order of US$1.6 billion. Due the complex political and security situation in Haiti, coupled with the global pandemic, a full in field mission was not considered feasible, so a hybrid mission was designed instead.

First, open-source information was collected and used to characterise the seismic event, analyse the strong ground motion and compare to established national and international earthquake codes and standard. Second, remote sensing techniques including Interferometric Synthetic Aperture Radar (InSAR) and Optical/Multispectral imagery were used to understand the earthquake mechanism, the ground displacement distribution and the possibility to detect landslide on a regional scale. The general applicability of remote sensing technique in the context of post disaster assessment was also evaluated. Finally, the earthquake impact on different building typologies in Haiti was investigated through the damage assessment of over 2000 buildings comprising schools, hospitals, churches and housing. This was done in collaboration with the Structural Extreme Events Reconnaissance (StEER) team, who mobilised a team of local non-experts to rapidly record building damage.

This talk summarises the mission setup and findings, and discusses the benefits of and difficulties encountered during this hybrid reconnaissance.

How to cite: Whitworth, M., Giardina, G., Penney, C., Di Sarno, L., Adams, K., Kijewski-Correa, T., Macabuag, J., Foroughnia, F., Macchiarulo, V., Ojaghi, M., Orfeo, A., Pugliese, F., Dönmez, K., Black, J., and d Aktas, Y.: Remote Reconnaissance Mission to the 14th August 2021 Haiti Earthquake; remote sensing and building damage assessments , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10192, https://doi.org/10.5194/egusphere-egu22-10192, 2022.