A selected dataset of the Iranian strong motion records

H. Zafarani () and M. R. Soghrat
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H. Zafarani: International Institute of Earthquake Engineering and Seismology (IIEES)
M. R. Soghrat: International Institute of Earthquake Engineering and Seismology (IIEES)

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2017, vol. 86, issue 3, No 16, 1307-1332

Abstract: Abstract Iranian strong motion records as well as detailed conditions of their instrument sites and the characteristics of their causative seismic sources are compiled and processed. The dataset consists of 2286 three-component records from 461 Iranian earthquakes with at least two high-quality records having moment magnitude from 3.9 to 7.3. These records are about 20% of the Iranian database and are suitable for seismic hazard analysis and engineering applications. Perhaps for the first time in the literature, the distance to the surface projection of the fault is reported for a great number of records corresponding to earthquakes with M > 6.0. The raw accelerations are processed using the wavelet de-noising method. Having corrected and filtered these raw data, the pseudospectral accelerations are calculated for each of the three components of time series, separately. In addition to the ground motion parameters, a large and comprehensive list of metadata characterizing the recording conditions of each record is also developed. Moreover, careful revision of the characteristics of the earthquakes such as location, magnitude, style of faulting and fault rupture plane geometry, if available, is carried out using the best available information in a scientifically sound manner. Finally, we also focus on special ground motion records including records with peak ground acceleration (PGA) >300 cm/s2 and distances less than 30 km. These are “exceptional” records in the Iranian dataset and include less than 2% of the selected dataset.

Keywords: Iran; Dataset; Strong ground motion; Seismic hazard (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11069-017-2745-2

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