Time - dependent seismic hazard assessment for the north and east Anatolian faults

Abstract

Until now, many probabilistic seismic hazard assessment (PSHA) studies have been performed for Turkey. However, except in a limited number of cases, character istic fault source modeling was not used. Since the North and East Anatolian Faults (NAF and EAF) have a tendency for rupturing in characteristic earthquakes, the first objective of this research is to develop a sound hybrid characteristic recurrence model for the NAF and EAF. The so-called hybrid model involves a composite characteris tic model (i.e., an exponential part for the smaller and a characteristic part for larger magnitudes) developed for each segment combined with a characteristic recurrence pro posed for multi-segment ruptures. Two different hybrid earthquake recurrence models with time - independent (or Poissonian) and time – dependent (or renewal) character istics are developed. By means of the renewal hybrid model, the effect of some seismic gaps along the NAF and EAF on seismic hazard is assessed, which is the primary purpose of the thesis. On the other hand, these two models have also given the oppor tunity to evaluate the results of the fully exponential model of the NAF and EAF. The comparison between different earthquake recurrence models developed for the NAF and EAF yields interesting results. Fully exponential model usually produces over estimated seismic hazard compared to the Poissonian hybrid – characteristic model. Slip deficits on some fault segments can increase the seismic hazard dramatically if the results of renewal hybrid model are considered. Although the overestimated results of fully exponential fault source model can compensate the high hazard based on renewal hybrid model, depending on the amount of slip deficit, the time – dependent hazard may exceed the hazard obtained by the fully exponential model. In cases where there is a considerable amount of slip deficit on a fault, a time - dependent seismic hazard model should be developed to deal with the worst-case scenario.