Statistical prediction of the next great earthquake around Tehran, Iran

Abstract

The analysis of seismic activity variations with space and time is a complex problem. Several statistical methods have been adopted to study these variations. One of the tasks that has attracted the attention of the seismological and statistical community is to explain seismicity patterns by statistical models and apply the results for earthquake prediction. Here the probability distribution of recurrence times as described by Exponential, Gamma, Lognormal, Pareto, Rayleigh and Weibull probability distributions and the idea of conditional probability has been applied to predict the next great (Ms ≥ 6.0 and Ms ≥ 6.5) earthquake around Tehran ( r ≤ 200 km). Conditional probability specifies the likelihood that a given earthquake will happen within a specified time. This likelihood is based on the information about past earthquake occurrences in the given region and the basic assumption that future seismic activity will follow the pattern of past activity. The rapid growth of Tehran to approximately 12 million inhabitants has resulted in a much more rapid increase in its vulnerability to natural disasters, especially earthquakes. Several earthquakes affected this region in the past, mostly on the Mosha, Taleqan, Eyvankey and Garmsar faults. The estimated recurrence times for Exponential, Gamma, Lognormal, Pareto, Rayleigh and Weibull distributions has been computed to be 66.64, 14.79, 26.88, 2.37, 67.58 and 80.47, respectively. Accordingly, one may expect that a large damaging earthquake may occur around Tehran approximately every 10 years.