Abstract
The probabilistic models achieved considerable attention in the field of seismology due to their dynamic properties. In this study, an attempt has been made to quantify the uncertainty observed in the earthquake data of the Hindu Kush region by using probabilistic models. The conditional probabilities of major earthquake (Mw ≥ 5.5) occurrence in the Hindu Kush region are estimated by using the Weibull, lognormal, gamma, and log-logistic probability distributions. The maximum likelihood estimation method has been used to estimate the model parameters. Results based on the three model selection criteria suggest that the Weibull and log-logistic distributions provide the most appropriate fit, while the lognormal and gamma distributions appeared as the second and third appropriate fitted distributions to the elapsed time data of the Hindu Kush region. Using the most appropriate fitted Weibull and log-logistic distributions, it has been observed that the estimated earthquake occurrence probability of magnitude 5.5 or greater in the Hindu Kush region reaches 0.94–0.99 within next 3 to 6 (2021–2024) years since the last event occurred in 2018 in the study region. The conditional probability values are continuously increasing with increasing time interval and it approximately reaches to one in next 6 to 12 (2024–2030) years without any elapsed time, i.e., (T = 0) years. The estimated earthquake conditional probability curves for different elapsed time and time interval values are also presented to understand the earthquake genesis in the study region. The earthquake mean recurrence interval is 0.68, 0.81, 0.68, and 1.11 years by using the Weibull, lognormal, gamma, and log-logistic models respectively. According to the obtained results, the earthquake of magnitude Mw ≥ 5.5 occurrence probability in the study region is significantly high. The obtained results provide important information’s regarding the underlying physical mechanism of earthquake generation process in the Hindu Kush region.
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