The earthquake cycle of the Manyi Fault, Tibet

This thesis focuses on the Manyi Fault in Northern Tibet which experienced a M_w 7.6 earthquake in 1997. The remoteness of the area limits the feasibility of measurements in the field, however the climate makes it ideal to study by remote sensing, specifically Interferometric Synthetic Aperture Radar (InSAR). The mechanics of the earthquake have been well documented however there are still numerous questions about the other stages of the earthquake cycle (postseismic and interseismic) across the fault. Previous studies of the postseismic motion across the Manyi Fault using four years of ERS SAR data show the deformation can be explained by either viscoelastic relaxation of a Standard Linear Solid body with a viscosity of 4x10¹⁸ Pa s or afterslip. We use the ERS timeseries and ratemaps formed from a network of ENVISAT SAR scenes from 2003-2010 to analyse the postseismic deformation. We create a series of afterslip models based on rate-and-state frictional laws, along with series of viscoelastic models with various rheologies (Maxwell and Burgers). Our results show that an afterslip model fits the data slightly better than a Burgers rheology but not within resolvable errors. A range of afterslip models fit the data well, with frictional parameters ranging from 8x10^-4 to 2x10^-3 and a preseismic slip rate of 8 to 20 mm/yr. The best-fitting Burgers rheology has a Kelvin element viscosity of 4x10¹⁸ Pa s and Maxwell element viscosity of 6x10¹⁹ Pa s. We analyse the interseismic InSAR signal observed before the 1997 earthquake using ERS data from 1992-1997 to find that the Manyi Fault was accumulating strain at 3+/-2 mm/yr. We also find the seismic locking depth was 22+/-15 km which correlates with the maximum depth of slip during the earthquake. We show there is no significant deformation across the fault to the north of the Manyi Fault which may be an extension to the Kunlun fault. We discuss an analytical 2D thin viscous channel model from literature that has been shown to match the data in this thesis. We show that, once errors are properly accounted for, their model cannot explain both the post and preseismic datasets.