S U M M A R YIn this study, based upon the calibrated specific barrier model (SBM) against the latest available strong motion data, ground motion prediction equations for soil and rock sites in northern Iran are developed. The SBM may provide the most complete, simple and self-consistent description of the faulting process, which is applicable in both 'near-fault' and 'far-field' regions. Consequently, the SBM may provide consistent ground motion simulations over the entire necessary frequency range and for all distances of engineering interests. To determine source parameters in this study, we used 163 three-component records of 32 earthquakes with magnitude ranging from M W 4.9 to 7.4 in northern Iran. In the database, records with hypocentral distances less than 200 km are chosen and only earthquakes whose moment-magnitude estimates are available have been used. Furthermore, using the best available information, recording sites are classified into two main geologic categories: rock and soil. Because of the lack of site amplification information in the most regions of the world including Iran, we used the H/V ratio method for estimating the site amplification. Moreover, the Kappa factor that shows diminishing the high-frequency amplitude is determined. In this study, two data sets are considered for determining the source parameters ( σ G and σ L ) and the H/V ratio and the Kappa factor. Only S-wave part of signals is used in each analysis. Regression analysis is performed using 'random effects' method that considers both interseismic (event-to-event) and coseismic (within-event) variabilities to effectively deal with the problem of weighting observations from different earthquakes. The residuals are controlled against available northern Iranian strong ground motion data to verify that the model predictions are unbiased and that there are no significant residual trends with magnitude and distance. At first, it is assumed that no sign of self-similarity breakdown is observed between the source radius and its seismic moment. After controlling the results, the modified SBM should be used as some deviations have been observed. To verify the robustness of the results, the number of observations is changed by removing various randomly selected data sets from the original database, which results in unchanged results of the model. Stochastic simulations are then implemented to predict peak ground motion and response spectra parameters. The stochastic SBM predictions are in relatively good agreement with other available attenuation relationships proposed for Iran, Europe and Middle East. It has been shown that the proposed SBM of this study provides unbiased ground motion estimates over the entire frequency range of most engineering applications. It provides a reliable and physically realistic, yet computationally efficient, way to model strong ground motions.

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Recent studies have shown that the vertical component of ground motion can be quite destructive on a variety of structural systems. Development of response spectrum for design of buildings subjected to vertical component of earthquake needs ground motion prediction equations (GMPEs). The existing GMPEs for northern Iranian plateau are proposed for the horizontal component of earthquake, and there is not any specified GMPE for the vertical component of earthquake in this region. Determination of GMPEs is mostly based on regression analyses on earthquake parameters such as magnitude, site class, distance, and spectral amplitudes. In this study, 325 three-component records of 55 earthquakes with magnitude ranging from M w 4.1 to M w 7.3 are used for estimation on the regression coefficients. Records with distances less than 300 km are selected for analyses in the database. The regression analyses on earthquake parameters results in determination of GMPEs for peak ground acceleration and spectral acceleration for both horizontal and vertical components of the ground motion. The correlation between the models for vertical and horizontal GMPEs is studied in details. These models are later compared with some other available GMPEs. According to the result of this investigation, the proposed GMPEs are in agreement with the other relationships that were developed based on the local and regional data.