Abstract
This study aims to develop a new earthquake strong motion-intensity catalog as well as intensity prediction equations for Iran based on the available data. For this purpose, all the sites which had both recorded strong motion and intensity values throughout the region were first searched. Then, the data belonging to the 306 identified sites were processed, and the results were compiled as a new strong motion-intensity catalog. Based on this new catalog, two empirical equations between the values of intensity and the ground motion parameters (GMPs) for the Iranian earthquakes were calculated. At the first step, earthquake “intensity” was considered as a function of five independent GMPs including “Log (PHA),” “moment magnitude (MW),” “distance to epicenter,” “site type,” and “duration,” and a multiple stepwise regression was calculated. Regarding the correlations between the parameters and the effectiveness coefficients of the predictors, the Log (PHA) was recognized as the most effective parameter on the earthquake “intensity,” while the parameter “site type” was removed from the equations since it was determines as the least significant variable. Then, at the second step, a simple ordinary least squares (OLS) regression was fitted only between the parameters intensity and the Log (PHA) which resulted in more over/underestimated intensity values comparing to the results of the multiple intensity-GMPs regression. However, for rapid response purposes, the simple OLS regression may be more useful comparing to the multiple regression due to its data availability and simplicity. In addition, according to 50 selected earthquakes, an empirical relation between the macroseismic intensity (I0) and MW was developed.
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The author would like to express his very great appreciation to Road, Housing and Urban Development Research center for accessing to the waveform of 140 three-component accelerograms of ISMN.
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Zare, M. Recent development of the earthquake strong motion-intensity catalog and intensity prediction equations for Iran. J Seismol 21, 591–613 (2017). https://doi.org/10.1007/s10950-016-9622-4
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DOI: https://doi.org/10.1007/s10950-016-9622-4