Journal of Geophysical Research : Solid Earth A Network Inversion Filter combining GNSS and InSAR for tectonic slip modeling

Studies of the earthquake cycle benefit from long-term time-dependent slip modeling, as it can be a powerful means to improve our understanding on the interaction of earthquake cycle processes such as interseismic, coseismic, postseismic, and aseismic slip. Observations from Interferometric Synthetic Aperture Radar (InSAR) allow us to model slip at depth with a higher spatial resolution than when using GNSS alone. While the temporal resolution of InSAR has typically been limited, the recent fleet of SAR satellites including Sentinel-1, COSMO-SkyMED, and RADARSAT-2 permits the use of InSAR for time-dependent slip modeling, at intervals of a few days when combined. With the vast amount of SAR data available, simultaneous data inversion of all epochs becomes challenging. Here, we expanded the original Network Inversion Filter to include InSAR observations of surface displacements in addition to GNSS. In the NIF framework, geodetic observations are limited to those of a given epoch, with a stochastic model describing slip evolution over time. The combination of the Kalman forward filtering and backward smoothing allows all geodetic observations to constrain the complete observation period. Combining GNSS and InSAR allows modeling of time-dependent slip at unprecedented spatial resolution. We validate the approach with a simulation of the 2006 Guerrero slow slip event. We highlight the importance of including InSAR covariance information, and demonstrate that InSAR provides an additional constraint on the spatial extent of the slow slip.

[1]  F. Cotton,et al.  Slow slip event in the Mexican subduction zone: Evidence of shallower slip in the Guerrero seismic g , 2013 .

[2]  Paul Segall,et al.  Imaging of aseismic fault slip transients recorded by dense geodetic networks , 2003 .

[3]  Paul Segall,et al.  A transient subduction zone slip episode in southwest Japan observed by the nationwide GPS array , 2003 .

[4]  Marie-Pierre Doin,et al.  Corrections of stratified tropospheric delays in SAR interferometry: Validation with global atmospheric models , 2009 .

[5]  P. Liu,et al.  Kinematic Inversion of the 2004 M 6.0 Parkfield Earthquake Including an Approximation to Site Effects , 2006 .

[6]  P. González,et al.  Error estimation in multitemporal InSAR deformation time series, with application to Lanzarote, Canary Islands , 2011 .

[7]  Dan Simon,et al.  Constrained Kalman filtering via density function truncation for turbofan engine health estimation , 2010, Int. J. Syst. Sci..

[8]  Paul A. Rosen,et al.  Co-seismic slip from the 1995 July 30 Mw= 8.1 Antofagasta, Chile, earthquake as constrained by InSAR and GPS observations , 2002 .

[9]  Tim J. Wright,et al.  A spatially variable power law tropospheric correction technique for InSAR data , 2015 .

[10]  Paul Segall,et al.  Time dependent inversion of geodetic data , 1997 .

[11]  C. Striebel,et al.  On the maximum likelihood estimates for linear dynamic systems , 1965 .

[12]  H. Zebker,et al.  Fault Slip Distribution of the 1999 Mw 7.1 Hector Mine, California, Earthquake, Estimated from Satellite Radar and GPS Measurements , 2002 .

[13]  Yehuda Bock,et al.  Frictional Afterslip Following the 2005 Nias-Simeulue Earthquake, Sumatra , 2006, Science.

[14]  A. Hooper,et al.  Recent advances in SAR interferometry time series analysis for measuring crustal deformation , 2012 .

[15]  Yehuda Bock,et al.  Southern California permanent GPS geodetic array: Spatial filtering of daily positions for estimating coseismic and postseismic displacements induced by the 1992 Landers earthquake , 1997 .

[16]  Thomas R. Walter,et al.  Time‐dependent volcano source monitoring using interferometric synthetic aperture radar time series: A combined genetic algorithm and Kalman filter approach , 2010 .

[17]  Rowena B. Lohman,et al.  Some thoughts on the use of InSAR data to constrain models of surface deformation: Noise structure and data downsampling , 2005 .

[18]  T. Wright,et al.  Statistical comparison of InSAR tropospheric correction techniques , 2015 .

[19]  P. Segall,et al.  A decadal‐scale deformation transient prior to the 2011 Mw 9.0 Tohoku‐oki earthquake , 2014 .

[20]  Ian Parsons,et al.  Surface deformation due to shear and tensile faults in a half-space , 1986 .

[21]  Paul Segall,et al.  Space time distribution of afterslip following the 2003 Tokachi‐oki earthquake: Implications for variations in fault zone frictional properties , 2004 .

[22]  Tim J. Wright,et al.  Reassessing the 2006 Guerrero slow‐slip event, Mexico: Implications for large earthquakes in the Guerrero Gap , 2015 .

[23]  M. Pardo,et al.  Shape of the subducted Rivera and Cocos plates in southern Mexico: Seismic and tectonic implications , 1995 .

[24]  T. Higuchi,et al.  A new approach to time-dependent inversion of geodetic data using a Monte Carlo mixture Kalman filter , 2003 .

[25]  R. Clayton,et al.  Interaction of Cocos and Rivera plates with the upper-mantle transition zone underneath central Mexico , 2014 .

[26]  Paul Segall,et al.  Network-based estimation of time-dependent noise in GPS position time series , 2015, Journal of Geodesy.

[27]  P. Tregoning,et al.  Slow slip events in Mexico revised from the processing of 11 year GPS observations , 2010 .

[28]  J. C. Savage A dislocation model of strain accumulation and release at a subduction zone , 1983 .

[29]  Tomoyuki Higuchi,et al.  Geodetic inversion for space–time distribution of fault slip with time-varying smoothing regularization , 2008 .

[30]  Marie-Pierre Doin,et al.  Systematic InSAR tropospheric phase delay corrections from global meteorological reanalysis data , 2011 .

[31]  Walter H. F. Smith,et al.  Free software helps map and display data , 1991 .

[32]  Haiying Gao,et al.  Source parameters and time‐dependent slip distributions of slow slip events on the Cascadia subduction zone from 1998 to 2008 , 2010 .

[33]  Andrew M. Bradley,et al.  Space‐time correlation of slip and tremor during the 2009 Cascadia slow slip event , 2011 .

[34]  Zhong Lu,et al.  Constraining the Slip Distribution and Fault Geometry of the Mw 7.9, 3 November 2002, Denali Fault Earthquake with Interferometric Synthetic Aperture Radar and Global Positioning System Data , 2004 .

[35]  John Langbein,et al.  Correlated errors in geodetic time series: Implications for time‐dependent deformation , 1997 .

[36]  L. Rivera,et al.  Coseismic Deformation from the 1999 Mw 7.1 Hector Mine, California, Earthquake as Inferred from InSAR and GPS Observations , 2002 .

[37]  Piyush Agram,et al.  A noise model for InSAR time series , 2015 .

[38]  J. Avouac,et al.  Inverting geodetic time series with a principal component analysis-based inversion method , 2010 .

[39]  P. Segall,et al.  Time‐dependent modeling of slow slip events and associated seismicity and tremor at the Hikurangi subduction zone, New Zealand , 2014 .

[40]  Michael Bevis,et al.  A high-resolution, time-variable afterslip model for the 2010 Maule Mw = 8.8, Chile megathrust earthquake , 2013 .

[41]  Paul Segall,et al.  Sudden aseismic fault slip on the south flank of Kilauea volcano , 2001, Nature.

[42]  F. Cotton,et al.  Spatial and temporal evolution of a long term slow slip event: the 2006 Guerrero Slow Slip Event , 2011 .

[43]  D. Melgar,et al.  Imaging the Moho and Subducted Oceanic Crust at the Isthmus of Tehuantepec, Mexico, from Receiver Functions , 2011 .

[44]  J. Beck,et al.  Accounting for prediction uncertainty when inferring subsurface fault slip , 2014 .

[45]  Piyush Agram,et al.  Multiscale InSAR Time Series (MInTS) analysis of surface deformation , 2011 .

[46]  Richard G. Gordon,et al.  Geologically current plate motions , 2010 .

[47]  Spatiotemporal evolution of aseismic interplate slip between 1996 and 1998 and between 2002 and 2004, in Bungo channel, southwest Japan , 2007 .

[48]  R. Bürgmann,et al.  Time‐dependent triggered afterslip following the 1989 Loma Prieta earthquake , 2000 .

[49]  Manoochehr Shirzaei,et al.  Time‐dependent model of creep on the Hayward fault from joint inversion of 18 years of InSAR and surface creep data , 2013 .

[50]  Heresh Fattahi,et al.  InSAR bias and uncertainty due to the systematic and stochastic tropospheric delay , 2015 .