Abstract: The development of high-rate GNSS seismology and seismic observation methods has provided technical support for acquiring the near-field real-time displacement time series during earthquake. But in practice, the limited number of GNSS continuous stations hardly meets the requirement of near-field quasi-real-time coseismic displacement observation, while the macroseismographs could be an important complement. Compared with high-rate GNSS, macroseismograph has better sensitivity, higher resolution(100~200Hz)and larger dynamic range, and the most importantly, lower cost. However, baseline drift exists in strong-motion data, which limits its widespread use. This paper aims to prove the feasibility and reliability of strong motion data in acquiring seismic displacement sequences, as a supplement to high-rate GNSS.
In this study, we have analyzed the strong-motion data of Wenchuan M_S8.0 earthquake in Longmenshan fault zone, based on the automatic scheme for empirical baseline correction proposed by Wang et al., which fits the uncorrected displacement by polynomial to obtain the fitting parameters, and then the baseline correction is completed in the velocity sequence. Through correction processing and quadratic integration, the static coseismic displacement field and displacement time series are obtained. Comparison of the displacement time series from the strong motions with the result of high-rate GPS shows a good coincidence. We have worked out the coseismic displacement field in the large area of Wenchuan earthquake using GPS data and strong motion data. The coseismic displacement fields calculated from GPS and strong motions are consistent with each other in terms of magnitude, direction and distribution patterns. High-precision coseismic deformation can provide better data constraint for fault slip inversion. To verify the influence of strong-motion data on slip distribution in Wenchuan earthquake, we used strong motion, GPS and InSAR data to estimate the stress drop, moment magnitude and coseismic slip model, and our results agreed with those of the previous studies. In addition, the inversion results of different data are different and complementary to some extent. The use of strong-motion data supplements the slip of the fault in the 180km segment and the 270~300km segment, thus making the inversion results of fault slip more comprehensive.
From this result, we can draw the following conclusions:1)Based on the robust baseline correction method, the use of strong motion data, as an important complement to high-rate GNSS, can obtain reliable surface displacement after the earthquake. 2)The strong motion data provide an effective method to study the coseismic displacement sequence, the surface rupture process and quick seismogenic parameters acquisition. 3)The combination of multiple data can significantly improve the data coverage and give play to the advantages of different data. Therefore, it is suggested to combine multiple data(GPS, strong motion, InSAR, etc.)for joint inversion to improve the stability of fault slip model.

Key words: strong-motion seismograph, baseline correction, high-rate GPS, coseismic deformation, slip inversion

摘要： GNSS连续站分布密度较低，难以满足地震近场位移准实时观测的需求，强震仪加速度记录可作为地表形变观测的重要补充手段。文中利用自动经验基线校正方法分析了汶川M_S8.0地震龙门山断裂带附近的震时强震数据，通过校正处理和2次积分得到了同震位移场分布。将强震仪所得的位移时间序列与高频GPS的结果进行对比分析，发现两者具有较好的一致性。强震仪与GPS计算的同震形变场在位移幅值、方向和总体分布特征方面较为接近。联合使用强震仪、GPS和InSAR数据，基于相同断层模型反演的断层滑动空间展布形态、滑动范围、滑动量、应力降和矩震级等与前人的研究成果均吻合较好。结果表明，强震记录可作为获取地震近场位移序列的有效手段，为研究地表破裂过程和地震参数快速获取提供有价值的基础资料。联合使用多种数据，可提高数据覆盖密度，实现数据优势互补。

关键词: 强震仪, 基线校正, 高频GPS, 同震形变, 滑动反演