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Relocation of the 2018 Zakynthos, Greece, aftershock sequence: spatiotemporal analysis deciphering mechanism diversity and aftershock statistics

Karakostas V., Kostoglou A., Chorozoglou D., Papadimitriou E.

Acta Geophysica

2020

Vol. 68, no. 5

1263--1294

An Mw 6.8 earthquake occurred on October 25, 2018, 35 km ofshore from the southwest coastlines of Zakynthos Island. The aftershock sequence appeared remarkably productive with six aftershocks of M≥5.0 in the frst month and tens of aftershocks with M≥4.0 during the study period. The GCMT solution for the main shock suggests a very low angle plane (dip=24°) for a dextral strike–slip faulting (rake=165°). A similar solution is suggested for the largest aftershock (Mw 5.9) that occurred 5 days afterward. The proximity of the main shock location with the dextral active boundary of Kefalonia Transform Fault Zone (KTFZ) along with the Hellenic Subduction front supports this oblique faulting. The aftershock activity is comprised mostly in depths 5–12 km and forms eight distinctive clusters that accommodate regional strain and evidence strain partitioning. The role of stress transfer and statistical analysis are combined for detailing the highly productive aftershock sequence. Earthquake networks analysis reveals their random structure soon after the main shock, which became small-world structure after the frst 200 days. Time series analysis constructed from the aftershock frequency and seismic moment release and manifested signifcant correlation among the eight seismicity clusters.

Application of complex network theory to the recent foreshock sequences of Methoni (2008) and Kefalonia (2014) in Greece

Chorozoglou D., Kugiumtzis D., Papadimitriou E.

Acta Geophysica

2017

Vol. 65, no. 3

543--553

Seismic hazard evaluation before recent strong main shocks in the area of Greece is attempted using prior seismicity on the basis of earthquake network theory. The connections of earthquake networks are constructed from successive earthquakes and the nodes are represented by cells of normal grids that were considered superimposed on the study areas. The dynamic evolution of the network structure is examined at sliding windows for identifying periods of statistically significant change, i.e., the network structure differentiation from that of a random network, where the structure is characterized by selected network measures, including the index of small-worldness property. By studying the structure of complex earthquake network, a distinct dynamic evolution is revealed, 2 months before the main shock occurrence. Particularly, the network measures, such as clustering coefficient and small-worldness index, tend to increase before and exhibit an abrupt jump at the time of the main shock occurrence, and then slowly decrease and become stable with small variations as before.