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Integrating GPS and InSAR to Measure Moment Rates along the San Andreas Fault System David T. Sandwell, Meng Wei, Xiaopeng Tong, Bridget Smith-Konter IGARSS, July 28, 2011
Integrating GPS and InSAR ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[data from JAXA and provided through the ASF; funding - NASA, Geodetic Imaging]
 
strain rate moment rate
Integrating GPS and InSAR ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[data from JAXA and provided through the ASF; funding - NASA, Geodetic Imaging]
strain rates from 16 groups
InSAR can resolve near-fault velocity need ~2 mm/yr precision
Integrating GPS and InSAR ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[data from JAXA and provided through the ASF; funding - NASA, Geodetic Imaging]
interseismic vector velocity model east north up [Smith-Konter and Sandwell, 2009]
locked zone Interseismic LOS Velocity high-pass filtered    < 40 km ALOS has the best  sensitivity to interseismic  motion. ERS ascending ERS descending ALOS ascending ALOS descending [Wei et al., 2010]
locked zone Interseismic LOS Velocity high-pass filtered    < 40 km Ascending ALOS  has 8-20 repeats ERS/Envisat ascending ERS/Envisat descending ALOS ascending ALOS descending poor correlation poor correlation too few repeats [Wei et al., 2010]
remove/restore this LOS model
align and stack with GMTSAR unwrap phase with snaphu [Chen and Zebker, 2002]
Integrating GPS and InSAR ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[data from JAXA and provided through the ASF; funding - NASA, Geodetic Imaging]
mean LOS  red  10 mm/yr blue -10mm/yr std  edit > 6 mm/yr
southern SAF  red  10 mm/yr blue -10mm/yr
southern SAF  red  10 mm/yr blue -10mm/yr
San Jacinto stepover  red  10 mm/yr blue -10mm/yr
San Jacinto stepover  red  10 mm/yr blue -10mm/yr
LA Basin  red  10 mm/yr blue -10mm/yr
LA Basin  red  10 mm/yr blue -10mm/yr
Parkfield SAF  red  10 mm/yr blue -10mm/yr
Parkfield SAF  red  10 mm/yr blue -10mm/yr
Creeping SAF  red  10 mm/yr blue -10mm/yr
Creeping SAF  red  10 mm/yr blue -10mm/yr
Creeping SAF  LOS error ~4 mm/yr
frame processing
frame processing
frame processing
frame processing
frame processing
frame processing
frame processing
frame processing
frame processing
frame processing
frame processing
Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object],[data from JAXA and provided through the ASF; funding - NASA, Geodetic Imaging]
interseismic model velocity strain  rate moment rate =  velocity depth = velocity X depth

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Integrating GPS and InSAR to Measure Strain Rates along San Andreas Fault

Notas del editor

  1. A more accurate indication of stress loading the earthquake cycle can be given by the coulomb stress rate Explore stress accumulation due to steady slip on downward extension of variably locked faults Fault orientation varies on a segment-by-segment basis, evaluated at 1/2 local locking depth. RL shear stress, extension +, uf is effective coef. Coulomb Stress accumulation rate, which is an indication of failure conditions due to the shear traction action on a plane and the plane’s resistance to failure Rates of interseismic stress range from 0.5 - 9 MPa/100yrs and are compatible to stress rates obtained through other methodologies [Harris and Simpson, 1998]. Coulomb stress accumulates fastest in regions of shallow locking depth and high slip rate, also true of strain rate studies [Wdowinski et al., 2001] Imperial, Brawley, Parkfield, and S. Calaveras all have shallow locking depths and are optimally orientated for high stress rate (4-9 MPa/100yrs). Rates also enhanced or reduced if the fault orientation is releasing or restraining. Lower accumulation rates occur along sections where slip is partitioned on multiple strands and where locking depth is considerably deeper. (~ 15+ km) Using rec. intervals compiled by paleo-group High rates also correlate with lower recurrence interval estimates. Calculate stress drop consistent with recurrence time x coulomb stress rate, plot for 1, 5, and 10 MPa Data lay primarily with the margins of 1-7 MPa stress drop Correlation is interesting, implying that over a characteristic time period, regions accumulate sufficient amounts of tectonic stress that result in large semi-periodic earthquakes with 1-7 MPa stress drops Results are largely independent of elastic layer or viscosity of substrate - very similar results to elastic half-space model Locking depth correlation -- suggests that the tectonically induced normal stress has an important influence on depth-averaged fault strength. , accounting for the interplay of shear and normal forces acting on a fault plane, the effects of friction, fault orientation and slip direction wrt overall plate motion vector. Not absolute stress -- need in situ measurements -- stress change due to coseismic slip or interseismic strain accumulation Shear and normal stress components are resolved on a fault plane of orientation
  2. Fault segments vary in the depth to which they are locked throughout the interseismic period of the earthquake cycle. Apparent locking depths on each segment are adjusted to match present-day GPS measurements The nearly 1000 estimates of horizontal velocity (SCEC GPS velocity model) + SOPAC provide relatively tight constraints on locking depths: 0-26 km. RMS deviation btwn model &amp; GPS velocity is 2.9 mm/yr (along-strike) and 1.8 mm/yr (across-strike) Large locking depths result in a broad interseismic deformation pattern, small locking depths result in a narrow pattern. While earthquake cycle effects are known to complicate estimates of true locking depth [Meade and Hager], apparent locking depth estimates, confirmed by seismicity depths, are well constrained by current GPS array