Investigation of earthquake recurrence networks: the cases of 2014 and 2015 aftershock sequences in Ionian Islands, Greece

D. Chorozoglou () and E. Papadimitriou ()
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D. Chorozoglou: Aristotle University of Thessaloniki
E. Papadimitriou: Aristotle University of Thessaloniki

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2020, vol. 102, issue 3, No 2, 783-805

Abstract: Abstract The investigation of earthquake recurrence networks that were constructed from two aftershock sequences in Greece, is performed, aiming to detect whether the structure of networks became distinct (non-random) before the occurrence of either the main shock or a major (strong) aftershock. The network nodes are the time series observations, which are the aftershocks magnitudes. Their binary connections are given by the arbitrary threshold $$\varepsilon$$ ε on the recurrence matrix, which is computed with the Heaviside function. Two aftershock sequences are the 2014 Kefalonia doublet, main shocks ( $$M = 6.1$$ M = 6.1 and $$M = 6.0$$ M = 6.0 ), and the 2015 Lefkada main shock ( $$M = 6.5$$ M = 6.5 ) sequence. The earthquake networks are formed for three different thresholds of $$\varepsilon$$ ε , for monitoring eight basic network measures and non-trivial properties such as the small world and scale free, and examining their structure during the evolution of the sequences. To assess whether the values of the eight network measures are statistically significant and the network gets non-trivial properties are present, the construction of randomized networks is required and then the comparison of the randomized network values with the ones from the original recurrence networks. The monitoring of network measures reveals that their original values diverge from the statistical significance, i.e., the structure of networks is random, immediately after the main shocks and shortly before the occurrence of the strongest aftershocks. On the contrary, in the intervening time, between the occurrences of main shocks and strongest aftershocks, their original values are statistically significant, which means that reveal the distinct network structure. The small-world and scale-free properties are sought but not revealed.

Keywords: Recurrence network; Time series; Small-world network; Scale-free network; Aftershock sequence; Greek seismicity (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11069-020-03915-y

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