Strong Ground Motion Prediction for Scenario Earthquakes

  • Masato TsurugiEmail author
Part of the Environmental Science and Engineering book series (ESE)


Strong ground motion is the most basic information to estimate seismic damage and examine the earthquake-resisting capacity of buildings. It’s very important to predict strong ground motions, estimate seismic damage and conduct earthquake countermeasures for a future large earthquake. Firstly, three basic components of seismic motions, i.e., source, path and site characteristics are mentioned to understand essence of method for strong ground motion prediction. Secondary, methods of strong ground motion prediction based on fault rupture propagation model such as empirical Green’s function method and stochastic Green’s function method are explained. In empirical Green’s function method, seismic motion from large earthquake is synthesized using that from small earthquake according to scaling laws of spatial and temporal growth of fault rupture. These are scaling laws of fault parameters for small and large earthquakes and the omega-squared source spectra. When there is no suitable observed record as Green’s function, stochastic Green’s function method can be adopted to predict strong ground motions. Instead of observed seismic motions from small earthquake, the method uses simulated motions as Green’s function and synthesizes seismic motions from a large earthquake using the same concepts of empirical Green’s function method. Thirdly, recipe for predicting strong ground motion from future large earthquakes is introduced. The recipe is summarized standard methodology for prediction of strong ground motions. The broadband strong ground motions can be predicted accurately by applying the recipe. Moreover, theoretical and empirical methods to evaluate path and site characteristics are explained. Finally, the stochastic Green’s function method is demonstrated on example of strong ground motion prediction for existing active fault in Iran.


Strong ground motion prediction Source–path–site characteristics Empirical Green’s function method Stochastic Green’s function method Recipe for predicting strong ground motions 



This chapter is presented with reference to some chapters written by emeritus Prof. Irikura in Kyoto University. I express gratitude to Prof. Irikura. The clarity and completeness of this chapter was improved by comment from Prof. Kagawa in Tottori University and Dr. Petukhin in Geo-Research Institute. The project for predicting strong ground motions from future large earthquake at Tabriz Bazaar was supported in part by the grant-in aid for Science Research from the Ministry of Education, Culture, Sports, Science and Technology, Japan (No. 21254001). Prof. Miyajima in Kanazawa University and Dr. Fallahi in Azerbaijan University of Shahid Madani lead the project energetically. I’m grateful to Prof. Miyajima and Dr. Fallahi. Ground structure model at Tabriz bazaar constructed by Dr. Yoshida in Fukui National College of Technology, and Dr. Solitani Jigheh in Azerbaijan University of Tarbiat Moallem. Generic mapping tool by Wessel and Smith (1998) was used for making several figures.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Geo-Research InstituteNishi-kuJapan

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