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Earthquake ground-motion prediction equations for northern Iran

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Abstract

Earthquake ground-motion prediction equations for soil and rock sites in northern Iran have been developed based on stochastic models and Bayesian updating. Due to a lack of recorded data, the well-known simulation methodology, finite-fault model, including estimates of the inherent uncertainty of ground-motion parameters, has been used for generating more than one thousand strong motions as input data. The Bayesian approach is an effective approach that allows the combination of knowledge of seismological theory with recorded data. Estimation of the prior information is one of the most controversial issues in a Bayesian approach. In this study, generated data based on the stochastic simulation model is first used to derive the prior coefficient of earthquake ground-motion prediction equations. The prior coefficients are updated within the Bayesian approach framework by using the recorded ground motion in northern Iran. The residual plots show that the updated prediction equations agree well with available northern Iran ground-motion data. Additionally, the proposed prediction equation is validated by comparing the estimated ground motion with those of recorded data at the observed stations.

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Acknowledgments

We thank the Building and Housing Research Centre of Iran for providing the accelerographic database. The authors would like to thank the anonymous reviewers whose valuable suggestions lead to significant improvements to this manuscript.

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  1. Department of Civil Engineering, University of Kurdistan, P.O. Box 416, Sanandaj, Iran

    Azad Yazdani & Milad Kowsari

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  1. Azad Yazdani
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Correspondence to Azad Yazdani.

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Yazdani, A., Kowsari, M. Earthquake ground-motion prediction equations for northern Iran. Nat Hazards 69, 1877–1894 (2013). https://doi.org/10.1007/s11069-013-0778-8

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