Integration of DInSAR and GPS for Co-seismic Modelling and Assessment of Potential Seismic Hazard

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Copyright: Kuang, Jianming
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Abstract
Earthquakes often cause the collapse of buildings and other structures over a large area, which severely threaten life and properties on the ground. Aftershock sequences or further triggered seismic events on other faults could continuously bring damage or threat to the vicinity of the epicentre area. GPS/GNSS can provide accurate measurements of surface deformation in three directions but only with point-based spatial coverage. Interferometric Synthetic Aperture Radar (InSAR), as a space-born imaging technique, can map ground deformation along the radar line-of-sight (LOS) direction over a large area with denser observations at centimetre level accuracy. With the recent development of new SAR satellite systems, more SAR acquisitions with higher spatial resolution and larger ground coverage can be obtained within a shorter period. However, InSAR is also limited by the insensitivity of measurements in the north-south direction due to the near-polar orbits of SAR satellites. Therefore, the integration of GPS and Differential Interferometric Synthetic Aperture Radar (DInSAR) allows us to obtain more information of the co-seismic deformation caused by earthquakes and to further optimize the co-seismic earthquake source modelling. In addition, large earthquakes always perturb the stress conditions of the surrounding fault systems, and the estimation of stress changes based on the source model is an essential hint of potential seismic hazard. This dissertation focuses on co-seismic modelling from the combination of DInSAR and GPS measurements, and the assessment of potential seismic hazard. Geodetic data from DInSAR and GPS measurements are used to invert source parameters and slip distribution of an earthquake based on the finite rectangle source fault in a homogeneous half-space. Furthermore, Coulomb stress change on the source fault and neighbouring active faults are estimated to evaluate the risk of seismic hazards. In this dissertation, three most recent large earthquakes were studied. First, the best-fit source models for the 2015 Mw 7.8 Nepal Earthquake and the following Mw 7.2 aftershock were inverted based on DInSAR and GPS data, revealing two NW-SE striking faults with low dips. The estimation of Coulomb stress change demonstrates that the Mw 7.2 event occurred on the high stress-loaded areas of the source fault for the main shock. Second, a normal single fault with a small left-lateral component was determined by co-seismic DInSAR and GPS measurements for the 2016 Mw 6.2 Amatrice (Central Italy) Earthquake. The stress changes induced by this event on the fault planes of the following two major shocks reveal that the triggering relationship between the Amatrice Earthquake and the following two events. Third, for the 2017 Mw 7.3 Kermanshah (Iran-Iraq border) Earthquake the optimised source model shows a blind reverse fault with a relatively large right-lateral component. The high spatial resolution images from SuperView-1 satellite reveal that most linear surface features mapped by DInSAR measurements are gravitational deformation. Also, the Coulomb stress change on the neighbouring active faults agrees with the occurrence of major aftershocks and suggests the risk of future earthquakes. This research reveals the better performance of the new generation of SAR satellites and demonstrates the seismic implication from co-seismic modelling.
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Author(s)
Kuang, Jianming
Supervisor(s)
Ge, Linlin
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Publication Year
2019
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Thesis
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Masters Thesis
UNSW Faculty
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