Strain Rate
The 3-D velocity maps derived from the InSAR/GNSS combination have small
spatial scale variations that are associated with hydrological processes
and residual atmospheric error. These models must be smoothed to extract
the underlying tectonic strain rate [e.g., Weiss et al.,2020]. This is accomplished by using a smoothing interpolator that has
constraints from elasticity to couple the two horizontal velocity
components [Haines and Holt, 1993] as implemented in the
program gpsgridder in GMT [Sandwell & Wessel , 2016].
We first subsample both the GNSS and InSAR/GNSS horizontal velocity
fields shown in Fig. 6 at a spacing of 2.5 km resulting in 40,016 2-D
velocity estimates. The gpsgridder algorithm uses singular value
decomposition of the elasticity Greens functions and we select only
those associated with the largest 800 eigenvalues. We then compute the
three horizontal strain rate components from the smoothed horizontal
velocities. The comparison of the GNSS only and InSAR/GNSS for several
components of strain rate (second invariant, maximum shear and
dilatation) are shown in Fig 7.
The San Andreas fault is well delineated by the concentrated high-strain
(> 200 nanostrain/yr). Compared to the prediction of the
GNSS-only strain rate model, the integrated InSAR/GNSS model reveals
larger strain concentration, especially at locations where there is
known surface creep (e.g., creeping section of SAFS and Hayward fault).
Maacama and Bartlett Springs both have much larger strain concentrations
in the InSAR/GNSS model although this may be a consequence of the
assumption that the InSAR deformation is parallel to the GNSS
deformation. Dilatational strain predicted by the integrated InSAR/GNSS
model shows extension in the Central Valley associated with the
subsidence from groundwater extraction. The shear component is also
larger in areas of known hydrological signals. There is a prominent
shear strain anomaly in the InSAR/GNSS strain rate maps (Fig. 7e, f)
that is to the east of and parallel to the creeping section. However,
there is not enough GNSS data in the region to determine if this is a
real strain-rate anomaly or artifact from the interpolation approach.
Overall, the strain is more widely distributed in the integrated
InSAR/GNSS model, with significant components being off-fault. The
remaining questions are how much of these are from tectonic motion and
how much from hydrological activities, and whether these off-fault
components are steady over time or just transients. Answering these will
be the key leading to accurate assessment of the strain/moment
accumulation and the associated seismic hazards.