Özet:

In this study, four different statistical distribution models (Weibull, Rayleigh, top and log-normal distribution models) were applied to calculate the conditional possibility of the Sivrice earthquake on January 24, 2020. For these calculations, repeated periods of M ≥4.7 earthquakes occurred in the region between 1900 and 2019 were used. The compatibility between the models and the data used is assessed by three different test criteria (Support Value (lnL), Akaike and Bayesian Information Criteria). Log-normal model is defined as the model that best represents work data. According to the results of the study, the conditional probabilities of the Sivrice earthquake (for t=0 and te=2); Log-normal model is estimated at 80 percent, upper model is 72, Weibull model is 70 percent, Rayleigh model is 36 percent.

Anahtar Kelimeler:

Özet:

In this study, the conditional probability of 24 January 2020 Sivrice (Elazığ) earthquake was calculated by applying four different statistical distribution models (Weibull, Rayleigh, exponential and log-normal distribution models). For these calculations, the recurrence periods of M≥4.7 earthquakes that occurred between 1900 and 2019 in the region were used. The fitting between the models and the data was evaluated with three different test criteria (Likelihood value (lnL), Akaike and Bayesian information criteria). Log-normal model was determined as the model that best represents the study data. According to the results of the study, the conditional probability values of the Elazig (Sivrice) earthquake (for t = 0 and te = 2) were calculated as 80% to the log-normal model, as 72% to the exponential model, as 70% to the Weibull model, and as 36% to the Rayleigh model.