Conditional Probabilities of Hellenic Arc Earthquakes Based on Different Distribution Models


ÇOBAN K. H. , Sayil N.

PURE AND APPLIED GEOPHYSICS, cilt.177, ss.5133-5145, 2020 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 177 Konu: 11
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1007/s00024-020-02576-z
  • Dergi Adı: PURE AND APPLIED GEOPHYSICS
  • Sayfa Sayıları: ss.5133-5145

Özet

The 27 November 2019M(w)6.0 earthquake that occurred in the southwestern part of the Hellenic Arc near Crete Island provided evidence of the high potential for strong earthquakes and active seismicity in the Hellenic Arc. In addition, tsunamis have been reported to occur for the region after major earthquakes in the historical past, so the seismic hazard of the Hellenic Arc should be evaluated in detail. The aim of this study is to evaluate the seismic hazard of the Hellenic Arc more reliably and accurately by estimating the conditional probabilities of a strong earthquake based on Weibull, gamma, log-normal, exponential, Rayleigh, and inverse Gaussian distribution models for the inter-event time ofM(w) >= 6.0 earthquakes that occurred between 1900 and 2019 in the study area. The fit between each model and the data was tested using four different test criteria, namely the log-likelihood value, Akaike information criterion, Bayesian information criteria, and Kolmogorov-Smirnov test. According to the results, the inverse Gaussian distribution was selected as the best, the log-normal distribution as the second best, the Weibull and gamma distributions as intermediate, and the Rayleigh and exponential distribution as the poorest and second poorest model, respectively. The conditional probability of an earthquake with magnitudeM(w) >= 6.0 is estimated to be higher than 0.70 according to all of the models used in this study for the base yeart(e) = 0 (t(e) = 2015) andt > 5 years (t > 2020). Moreover, the results obtained based on the inverse Gaussian, exponential, log-normal, and Weibull distribution models are close to each other and are higher than 0.60 fort(e) = 0 andt >= 3 years (t >= 2018). The outcomes of this study when using the different distribution models will contribute to assessments of the seismic as well as tsunami hazards for the region.