A study of short-term spatiotemporal clustering features of Greek seismicity

Kourouklas, Christos; Mangira, Ourania; Iliopoulos, A. C.; Chorozoglou, D.; Papadimitriou, Eleftheria

doi:10.1007/s10950-020-09928-1

Cited by 8 publications

(4 citation statements)

References 63 publications

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“…Furthermore, the productivity parameter, α, was estimated equal to α = 1.78, indicating also Mainshock-Aftershock type of sequence, since Mainshock-Aftershock activity is typically characterized by α values ranging between [1.3-3.1], whereas swarm-like activity is ascribed to values ranging between [0.35-0.85] (Hainzl and Ogata, 2005;Ogata, 1992). The parameters expressing temporal characteristics, c and p, attain expected values, in comparison with those reported in previous studies ranging from 0.03 to 0.07 and from 1.16 to 1.25, respectively (Chu et al, 2011;Kourouklas et al, 2020).…”

Section: Temporal Features From the Etas Model Fittingmentioning

confidence: 45%

Spatiotemporal characteristics and earthquake statistics of the 2020 and 2022 adjacent earthquake sequences in North Aegean Sea (Greece)

Bonatis,

Karakostas,

Kourouklas

et al. 2024

Seismica

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The two moderate earthquakes that occurred close and to the north of the North Aegean Trough (NAT) on 26 September 2020 (Mw5.3) and 16 January 2022 (Mw5.4), both followed by aftershock activity, are examined. Seismic activity along the NAT and its parallel branches is continuous and remarkable, with numerous strong instrumental (M≥6.0) earthquakes. Yet, the frequency of moderate (5.0≤M<6.0) earthquakes outside these major fault branches is rather rare and therefore their investigation provides the optimal means to decipher the seismotectonic properties of the broader area. The temporal and spatial proximity of the two seismic excitations from late September of 2020 through early 2022, intrigues for exhaustive investigation of seismic activity with the employment of earthquake relocation techniques, moment tensor solutions and statistical analysis. Our research revealed that this seismic activity purely falls inside the Mainshock – Aftershock type, with fast aftershock decay rates and moderate productivity. According to our findings, the two seismic sequences, despite their close proximity, exhibit distinctive features as a result of the intricate stress field generated at the western termination of the NAF system in an extensional domain.

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Section: Temporal Features From the Etas Model Fittingmentioning

confidence: 45%

Spatiotemporal characteristics and earthquake statistics of the 2020 and 2022 adjacent earthquake sequences in North Aegean Sea (Greece)

Bonatis,

Karakostas,

Kourouklas

et al. 2024

Seismica

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“…This study revealed that the joint implementation of physics-based approaches and the statistical ETAS model is beneficial for future OEF systems. Kourouklas et al (2020) Mangira et al (2020), revealing that the employed ETAS clustering model provides reliable forecasts of the aftershock activity for this region.…”

Section: Region Of Studymentioning

confidence: 90%

Variations in hazard during earthquake sequences between 1995 and 2018 in western Greece as evaluated by a Bayesian ETAS model

Azarbakht¹,

Ebrahimian

Jalayer

et al. 2022

Geophysical Journal International

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Summary Forecasting the spatio-temporal occurrence of events is at the core of Operational Earthquake Forecasting, which is of great interest for risk management, particularly during ongoing seismic sequences. Epidemic type aftershock sequence (ETAS) models are powerful tools to estimate the occurrence of events during earthquake sequences. In this context, a robust seismicity forecasting framework based on Bayesian-inference has been adapted to the Patras and Aegio region in western Greece (one of the most seismically active parts of Mediterranean), and an incremental adaptive algorithm is introduced to train the priors for ETAS model parameters. The seismicity forecasting is capable of accounting for uncertainty in the model parameters as well as variations in the sequence of events that may happen during the forecasting interval. Six seismic sequences between 1995 and 2018 were selected with mainshock moment magnitudes Mw ≥ 6.0. The ETAS model was adapted for each seismic sequence. The number of forecasted events with Mw≥4.5 and their spatial distribution was retrospectively compared with the as-recorded earthquake catalogue, confirming a good agreement between the forecasts and observations. The results show that the adapted model can be employed immediately after a severe mainshock to statistically predict potentially damaging earthquakes during the ongoing seismic sequence. The seismicity forecasts were translated to short-term daily exceedance rates for different thresholds of peak ground acceleration. The results reveal that the seismic hazard increased by up to 33 times in the case of the damaging 1995 Mw 6.5 earthquake in the city of Aegio. However, the results confirmed that in all six studied sequences, the increased seismic hazard decayed rapidly during the two days after the mainshock, and remained relatively high in the following days (roughly ten times the long-term time-independent hazard).

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“…According to the study by 17 , the ETAS model is the best model for describing short-term seismicity (see also 18 ). The ETAS model performed quite well in prospectively forecasting the seismicity within various operational frameworks in California, Greece, Italy, Japan, Spain, New Zealand, and Iceland 6,[18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33] . It has been employed for time-dependent seismic hazard 8,24,32,34,35 , and risk and loss forecasting 8,34,[36][37][38][39] .…”

Section: Introductionmentioning

confidence: 99%

Improvements to seismicity forecasting based on a Bayesian spatiotemporal ETAS model: Application to 2017-2019 Kermanshah seismic sequence in Western Iran

Ebrahimian

Jalayer

Asayesh

et al. 2022

Preprint

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The epidemic-type aftershock sequence (ETAS) model provides an effective tool for predicting the spatio-temporal evolution of aftershock clustering in short-term. Based on this model, a fully probabilistic procedure was previously proposed by the first two authors for providing spatio-temporal predictions of aftershock occurrence in a prescribed forecasting time interval. This procedure exploited the versatility of the Bayesian inference to adaptively update the forecasts based on the incoming information provided by the ongoing seismic sequence. In this work, this Bayesian procedure is improved: (1) the likelihood function for the sequence has been modified to properly consider the piecewise stationary integration of the seismicity rate; (2) the spatial integral of seismicity rate over the whole aftershock zone is calculated analytically; (3) background seismicity is explicitly considered within the forecasting procedure; (4) an adaptive kernel Markov Chain Monte Carlo simulation procedure is adopted; (5) leveraging the stochastic sequences generated by the procedure in the forecasting interval, the N-test and the S-test are adopted to verify the forecasts. This framework is demonstrated and verified through retrospective early forecasting of seismicity associated with the 2017-2019 Kermanshah seismic sequence activities in western Iran in two distinct phases following the main events with Mw7.3 and Mw6.3, respectively.

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A study of short-term spatiotemporal clustering features of Greek seismicity

Cited by 8 publications

References 63 publications

Spatiotemporal characteristics and earthquake statistics of the 2020 and 2022 adjacent earthquake sequences in North Aegean Sea (Greece)

Spatiotemporal characteristics and earthquake statistics of the 2020 and 2022 adjacent earthquake sequences in North Aegean Sea (Greece)

Variations in hazard during earthquake sequences between 1995 and 2018 in western Greece as evaluated by a Bayesian ETAS model

Improvements to seismicity forecasting based on a Bayesian spatiotemporal ETAS model: Application to 2017-2019 Kermanshah seismic sequence in Western Iran

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