IAG-IASPEI 2017

講演情報

Oral

IASPEI Symposia » S07. Strong ground motions and Earthquake hazard and risk

[S07-1] Amplification of ground motions and GMPEs

2017年7月31日(月) 08:30 〜 10:00 Main Hall (Kobe International Conference Center 1F)

Chairs: John Clinton (ETH Zurich) , Masumi Yamada (Kyoto University)

08:45 〜 09:00

[S07-1-02] Estimation of Source, Path and Site Effects in Hangay region Mongolia using a dense broadband seismic array

Baigalimaa Ganbat1, Toshiaki Yokoi2, Takumi Hayashida2 (1.Institute of Astronomy and Geophysics of Mongolian Academy Science, Ulaanbaatar, Mongolia, 2.The Building Research Institute,Tsukuba, Japan)

We applied a spectral inversion method to data from a broadband seismic array in Hangay region, Mongolia to estimate source, local site and propagation path effects. The 72-stations database comprises a total of 1331 waveforms from 32 earthquakes (3.0 < Ml < 5.6). To secure the accuracy of hypocenter locations, first we relocated hypocenters using the detected P-wave arrival times. The averaged P and S-wave velocities estimated from the relocated hypocenters are 6.1 km/s and 3.5 km/s, which corresponds well to those of upper crust model (CRUST 2.0). We also obtained seismic moment and focal mechanism of each earthquake based on the time-domain moment tensor inversion and P-wave polarities. The results show that strike-slip faults are dominant in the target region and estimated magnitudes range from Mw 2.9 to Mw 4.5. In the spectral inversion method, we applied two kinds of approaches, which use reference site and reference events in the inverse problem for computational stability. We found that two different inversion approaches gave similar results in the frequencies range between 0.5 and 10 Hz. The predominant frequencies at each site correspond well to those from horizontal-to-vertical (H/V) spectral ratios of S-wave portion. Finally we estimated seismic moment, corner frequency and static stress drop for each event using our inversion results. Our results indicate that a large amount of dataset from the dense seismic network provides fundamental and useful information for seismic hazard assessment in this region.