|Title||Fault geometry inversion and slip distribution of the 2010 M-w 7.2 El Mayor-Cucapah earthquake from geodetic data|
|Publication Type||Journal Article|
|Year of Publication||2017|
|Authors||Huang M.H, Fielding E.J, Dickinson H., Sun J.B, Gonzalez-Ortega J.A, Freed A.M, Burgmann R.|
|Journal||Journal of Geophysical Research-Solid Earth|
|Type of Article||Article|
|Keywords||coseismic slip; displacements; earthquake; El Mayor-Cucapah earthquake; geodetic inversion; gps observations; hector; InSAR; landers; layered model; mine; near-field; postseismic deformation; shallow slip deficit; southern california; static inversion with; surface rupture|
The 4 April 2010 M-w 7.2 El Mayor-Cucapah (EMC) earthquake in Baja, California, and Sonora, Mexico, had primarily right-lateral strike-slip motion and a minor normal-slip component. The surface rupture extended about 120km in a NW-SE direction, west of the Cerro Prieto fault. Here we use geodetic measurements including near- to far-field GPS, interferometric synthetic aperture radar (InSAR), and subpixel offset measurements of radar and optical images to characterize the fault slip during the EMC event. We use dislocation inversion methods and determine an optimal nine-segment fault geometry, as well as a subfault slip distribution from the geodetic measurements. With systematic perturbation of the fault dip angles, randomly removing one geodetic data constraint, or different data combinations, we are able to explore the robustness of the inferred slip distribution along fault strike and depth. The model fitting residuals imply contributions of early postseismic deformation to the InSAR measurements as well as lateral heterogeneity in the crustal elastic structure between the Peninsular Ranges and the Salton Trough. We also find that with incorporation of near-field geodetic data and finer fault patch size, the shallow slip deficit is reduced in the EMC event by reductions in the level of smoothing. These results show that the outcomes of coseismic inversions can vary greatly depending on model parameterization and methodology.