SELECTION OF GROUND MOTION PREDICTION EQUATIONS FOR SEISMIC HAZARD ANALYSES IN MAKRAN REGION, IRAN

سال انتشار: 1398
محل انتشار: هشتمین کنفرانس بین المللی زلزله شناسی و مهندسی زلزله
کد COI اختصاصی: SEE08_007
زبان مقاله: انگلیسی
تعداد مشاهده: 754

نویسندگان

Associate Professor, International institute of earthquake engineering and seismology (IIEES), Tehran, Iran

Phd, International institute of earthquake engineering and seismology (IIEES), Tehran, Iran

چکیده

Ground motion prediction equations (GMPEs) have a key role in evaluating the intensity measures (for example, PGA, PGV or SA) for seismic hazard assessment in a given region. Since different GMPEs have been developed based on local, regional and global databases, the selection of the appropriate equations is necessary to reduce the uncertainty. According to tectonic characteristics in the Makran region, different categories of GMPEs are required for seismic hazard assessment including GMPEs for shallow crustal events and subduction zone earthquakes (in-slab and interface events).In this study, the selected dataset consists of 314 records from 80 earthquakes. The dataset is used for statistical analyses and modification of the GMPEs. Noted that, the earthquakes are classified in two groups including shallow earthquakes (the events with focal depth less than 40 km; 67 events and 210 records) and in-slab ones (with the depth more than 40 km; 13 events and 104 records). There are no recorded data in the region for interface earthquakes in the studied region. About 11 GMPEs (developed based on local, regional and global data) are candidate for selection and modification in the studied region based on shallow earthquakes. In addition, five relations are used in the analyses for in-slab events. Different statistical analyses have been applied to show the performance of GMPEs for applicability in the region. The results show that the modification term applied in the GMPEs caused significant performance in the applicability of the relations.

کلیدواژه ها

GMPEs, Iran, Makran, Statistical analyses, Adjustment factors

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