Earth and Space Science (Jan 2024)

A New Method to Invert for Interseismic Deep Slip Along Closely Spaced Faults Using Surface Velocities and Subsurface Stressing‐Rate Tensors

  • H. Elston,
  • M. Cooke,
  • J. Loveless,
  • S. Marshall

DOI
https://doi.org/10.1029/2023EA003069
Journal volume & issue
Vol. 11, no. 1
pp. n/a – n/a

Abstract

Read online

Abstract Inversions of interseismic geodetic surface velocities often cannot uniquely resolve the three‐dimensional slip‐rate distribution along closely spaced faults. Microseismic focal mechanisms reveal stress information at depth and may provide additional constraints for inversions that estimate slip rates. Here, we present a new inverse approach that utilizes both surface velocities and subsurface stressing‐rate tensors to constrain interseismic slip rates and activity of closely spaced faults. We assess the ability of the inverse approach to recover slip rate distributions from stressing‐rate tensors and surface velocities generated by two forward models: (a) a single strike‐slip fault model and (b) a complex southern San Andreas fault system (SAFS) model. The single fault model inversions reveal that a sparse array of regularly spaced stressing‐rate tensors can recover the forward model slip distribution better than surface velocity inversions alone. Because focal mechanism inversions currently provide normalized deviatoric stress tensors, we perform inversions for slip rate using full, deviatoric or normalized deviatoric forward‐model‐generated stressing‐rate tensors to assess the impact of removing stress magnitude from the constraining data. All the inversions, except for those that use normalized deviatoric stressing‐rate tensors, recover the forward model slip‐rate distribution well, even for the SAFS model. Jointly inverting stressing rate and velocity data best recovers the forward model slip‐rate distribution and may improve estimates of interseismic deep slip rates in regions of complex faulting, such as the southern SAFS; however, successful inversions of crustal data will require methods to estimate stressing‐rate magnitudes.

Keywords