Dense strong motion and high-rate Global Navigation Satellite Systems (GNSS) networks have been deployed in central Italy for rapid seismic source determination and corresponding hazard mitigation. Different from previous studies for the consistency between two kinds of sensor at collocated stations, here we focus on the combination of high-rate GNSS displacement waveforms with collocated seismic strong motion accelerators, and investigate its application to image rupture history. Taking the 2016 August 24 Mw 6.1 Central Italy earthquake as a case study, we first generate more accurate and longer period seismogeodetic displacement waveforms by a Kalman filter, then model the rupture behaviour through a joint inversion including seismogeodetic waveforms and InSAR observations. Our results reveal that strong motion data alone can overestimate the magnitude and mismatch the GNSS observations, while 1 Hz sampling rate GNSS is insufficient and the displacement is too noisy to depict rupture process. By contrast, seismogeodetic data enhances temporal resolution and maintains the static offsets that provide vital constraint to the reliable estimation of earthquake magnitude. The obtained model is close to the jointly inverted one. Our work demonstrates the unique usefulness of seismogeodesy for fast seismic hazard response.
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Chen et al. (2018) studied this question.
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