Assessment of Earthquake Recurrence for North India and Surrounding Region Using Probabilistic Models

Abstract

AbstractThe northern part of India is one of the seismically active regions of the world, which lies near the plate boundary region of Indian plate and Eurasian plate. The continuous tectonic movement between Indian plate and Eurasian plate accumulates lots of strain energy in the plate boundary region and this energy may come out in near or far future generating big earthquakes in this region. The 25thApril 2015 Nepal earthquake (Mw 7.8) is one of the outcomes of such huge stored strain energy. So, in the attempt of minimizing loss of lives and properties, this paper presents probabilistic models for forecasting of earthquakes of magnitude (Mw) ≥ 7.0 in North India (NI) and surrounding region. In this present study, three probabilistic models namely Weibull, Gamma and Lognormal probabilistic models were used to estimate the probability of occurrence of earthquake Mw ≥ 7.0 using an earthquake catalogue 1900–2016. The goodness of models was assessed by the logarithmic likelihood function (ln L). As per the results, the Weibull models shows highest probability of occurrence whereas the lognormal model shows the lowest probability of occurrence. The estimated conditional probability reaches 0.999 after a time interval of 11, 13 and 15 years for Weibull, Gamma and lognormal Distribution respectively from the last earthquake of 2015. This means by the year 2026, 2028 and 2030 by Weibull, Gamma and lognormal model respectively will achieve a conditional probability of 99.9% in and around the present study area.KeywordsConditional probabilityEarthquake recurrenceMaximum likelihood estimation (MLE)Probability modelsRecurrence interval