COSEISMIC DISPLACEMENT FIELD OF THE WENCHUAN EARTHQUAKE DERIVED FROM STRONG MOTION RECORDS AND APPLICATION IN SLIP INVERSION

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.