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机构地区:[1]中国地震局兰州地震研究所,甘肃兰州730000 [2]北京市地震局,北京100080
出 处:《地震工程学报》2013年第3期425-431,共7页China Earthquake Engineering Journal
基 金:兰州地震研究所科技发展基金面上项目(2011M03);地震行业科研专项课题(201208009)
摘 要:使用甘肃省测震台网记录的三分向宽频带长周期数字波形资料在时间域反演了2013年7月22日甘肃岷县MS6.6地震的矩张量解,并与Harvard大学CMT解进行了比较。最后结合该地区的地质资料和构造背景分析了岷县地震发震成因,对可能的发震断层进行了讨论。On July 22, 2013, the Minxian magnitude 6.6 earthquake occurred beneath the north- east margin of the Tibetan plateau, Gansu, China. The earthquake and its aftershocks caused considerable damages, including more than 95 casualties, 2414 injuries, and approximately 17.5 billion yuan in property damage. More information on the source properties of such events can help to characterize fault the structures, which can contribute to an improved understanding of the hazards associated with future great earthquakes. As of August 28, 13:35, aftershocks have been recorded by the Gansu seismology network, including a magnitude 5.6 event following the mainshock. We analyzed the broadband waveforms for the mainshock with sufficient signal-to- noise levels to invert for seismic moment tensors. All stations involved in this study are broad- band stations situated near the July 22 mainshock; data showing such problems as misorientation of horizontal components, mislabeling, and polarity reversal in one or more components (Niu et al. , 2010) were removed. During the data processing, we removed the mean value and instru- ment response, detrended the waveforms, integrated the three-component velocity waveforms to displacement, and rotated the horizontal components to the radial and tangential directions. Be- fore performing moment tensor inversion, waveforms were filtered with a Butterworth filter with frequencies between 0. 016 Hz and 0.05 Hz. On the basis of the Crust 2.0 global crustal model, and considering the heterogeneity of the crust and the distances to the recording stations, various velocity models for each station were employed to account for variabilities in the crustal structure.To insure the quality of the results of the inversion process, we retained only the station with va- riance reduction (VR) is ≥ 80, and got 6 stations for the inversion. After depth iteration, the best solutions obtained at a depth of 8 km were 87, 13, and 93 for double couple (DC}, the com- pensated linear vector dipole (CLVD�
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