Potential and limits of InSAR to characterize interseismic deformation independently of GPS data: Application to the southern San Andreas Fault system
- Author(s): Chaussard, E
- Johnson, CW
- Fattahi, H
- Bürgmann, R
- et al.
Published Web Locationhttps://doi.org/10.1002/2015GC006246
© 2016. American Geophysical Union. All Rights Reserved. The evaluation of long-wavelength deformation associated with interseismic strain accumulation traditionally relies on spatially sparse GPS measurements, or on high spatial-resolution InSAR velocity fields aligned to a GPS-based model. In this approach the InSAR contributes only short-wavelength deformation and the two data sets are dependent, thereby challenging the evaluation of the InSAR uncertainties and the justification of atmospheric corrections. Here we present an analysis using 7 years of Envisat InSAR data to characterize interseismic deformation along the southern San Andreas Fault (SAF) and the San Jacinto Fault (SJF) in southern California, where the SAF bifurcates onto the Mission Creek (MCF) and the Banning (BF) fault strands. We outline the processing steps for using InSAR alone to characterize both the short- and long-wavelength deformation, and evaluate the velocity field uncertainties with independent continuous GPS data. InSAR line-of-sight (LOS) and continuous GPS velocities agree within ∼1-2 mm/yr in the study area, suggesting that multiyear InSAR time series can be used to characterize interseismic deformation with a higher spatial resolution than GPS. We investigate with dislocation models the ability of this mean LOS velocity field to constrain fault slip rates and show that a single viewing geometry can help distinguish between different slip-rate scenarios on the SAF and SJF (∼35 km apart) but multiple viewing geometries are needed to differentiate slip on the MCF and BF (<12 km apart). Our results demonstrate that interseismic models of strain accumulation used for seismic hazards assessment would benefit from the consideration of InSAR mean velocity maps.