Crustal Deformation Research at UHM 

Lithospheric Deformation and Stress Evolution of the San Andreas Fault System SAF stress movie
Sliced view of Coulomb stress accumulation model of the San Andreas Fault System based on interseismic stress accumulation rates and stress changes from 100+ historical and prehistorical earthquake ruptures. Color scale is saturated at 4 MPa to emphasize significant regions of accumulated stress. Stress variations with depth are due to transitions in along-strike locking depth. 
2019 Mw7.1 Ridgecrest Earthquake
2018 Kilauea Deformation
Tidal Stress &
Faulting of Ganymede, Enceladus & Europa
3-D Elastic & Viscoelastic
Crustal Deformation Modeling
GPS & InSAR Applications



Lithospheric Deformation & Stress Evolution of the San Andreas Fault System


The primary objective of our groupʻs research is to improve our understanding of the earthquake cycle through sophisticated computer models of fault system deformation constrained by geologic, geodetic, and seismic data.   Plate boundary interactions, like those characterizing the behavior of the San Andreas Fault System, have been vigorously deforming much of the Earth's crust for over the past several million years.   Recognized as the most widely researched fault system in the world, the San Andreas has become a natural laboratory for investigating the many facets of plate boundary deformation revealed by a synthesis of geologic, geodetic, and seismic observations. 

To model lithospheric deformation of the San Andreas Fault System associated with the earthquake cycle, my group uses a semi-analytical Fourier model that calculates the 3D response of both elastic and viscoelastic mediums to a distribution of body forces. Merging data from the historical & prehistorical earthquake database with geologic and geodetic observations, these models allows for both large-scale and long-term deformation simulations of the earthquake cycle.   To date, we have used this method to investigate 1000-year earthquake scenario models of the San Andreas Fault System. Stress evolution models, simulating interseismic, coseismic, and postseismic changes over the past 400 years, were also constructed based on these findings.

Related Publications:

Smith-Konter, B; L. Burkhard, L. Ward, X. Xu, P. Wessel, and D.T. Sandwell (2020), San Andreas Fault System stress evolution (1600-2020),  https://doi.org/10.6084/m9.figshare.12900005.

Xu, X., L. Ward, J. Jiang, B. Smith-Konter, E. Tymofyeyeva, E. O. Lindsey, A. G. Sylvester and D.T. Sandwell (2018), Surface creep rate of the Southern San Andreas Fault modulated by stress perturbations from nearby large events, Geophys. Res. Lett., doi: 10.1029/2018GL080137.

Luttrell, K. and B. Smith-Konter (2017), Limits on crustal differential stress in southern California from topography and earthquake focal mechanisms, Geophys J. Int., doi: 10.1093/gji/ggx301.

Howell, S., B. Smith-Konter, N. Frazer, X. Tong, and D.T. Sandwell (2015), The vertical fingerprint of earthquake-cycle loading in Southern California, Nature Geosciences, doi: 10.1093/2015-03-04591.

Tong, X., D.T. Sandwell, and B. Smith-Konter (2015), An integral method to estimate the moment accumulation rate on the Creeping Section of the San Andreas Fault, Geophys. J. Int., doi: 10.1093/gji/gjis140783.

Smith-Konter, B., G.M. Thornton, and D.T. Sandwell (2014), Vertical crustal displacement due to interseismic deformation along the San Andreas fault: Constraints from tide gauges, Geophys. Res. Lett., doi:10.1029/2014GL060091.

Del Pardo, C., B. Smith-Konter, C.Kreemer, G. Blewitt, W. Hammond, and L. Serpa (2012), Interseismic deformation and stress evolution of the Death Valley Fault Zone, J. Geophys. Res., 117, B060404, doi:10.1029/2011JB008552.

Smith-Konter, B., D. Sandwell, and P. Shearer (2011), Locking depths estimated from geodesy and seismology along the San Andreas Fault System:  Implications for seismic moment release, J. Geophys. Res., 116, B06401, doi:10.1029/2010JB008117.

Smith-Konter, B., D. Sandwell, and M. Wei (2010), Integrating GPS and InSAR to resolve stressing rates of the SAF System, EarthScope inSights Newsletter, Summer 2010.

Wei, M., D. Sandwell, and Smith-Konter, B. (2010), Optimal combination of InSAR and GPS for measuring interseismic crustal deformation, J. Adv. in Space Res., doi: 10.1016/j.asr.2010.03.013.

Smith-Konter, B., and D.T. Sandwell (2009), Stress evolution of the San Andreas Fault System: Recurrence interval versus locking depth, Geophys. Res. Lett., 36, doi:10.1029/2009GL037235.

Luttrell, K., D.T. Sandwell, B. Smith-Konter, B. Bills, and Y. Bock (2007), Modulation of the earthquake cycle at the southern San Andreas fault by lake loading, Journal of Geophysical Research, 112, doi:10.1029/2006JB004752.

Smith, B.R. and D.T. Sandwell (2006), A model of the earthquake cycle along the San Andreas Fault System over the past 1000 years, J. Geophys. Res., 111, doi:10.1029/2005JB003703.

Smith, B. R. and D. T. Sandwell (2003), Coulomb stress along the San Andreas Fault System, J. Geophys. Res., 108, doi:10.1029/2002JB002136.


View  animated models:



SAF vertical earthquake cycle

(Left) Vertical velocities of the San Andreas Fault System predicted by model selection (statistical, s-model) using GPS data and the best-fitting physical deformation model (p-model) simulating the vertical crustal response of earthquake cycle loading at depth throughout the past 300+ years. (Right) Map view representation of interseismic quadrant lobate patterns of vertical motion from bending moments induced by variations in fault locking (or creeping) depth.  From Howell et al. (2016).

SAF Historical earthquakes

Modeled historical earthquake ruptures (Mw6.0) of the San Andreas Fault System from 1800 to 2010 [Jennings, 1994; Toppozada et al., 2002]. Colors depict era of earthquake activity from 1800 to 1850 (red), 1850 to 1900 (yellow), 1900 to 1950 (green), and 1950 to 2004 (blue). Grey octagons represent locations of paleoseismic sites.  From Smith and Sandwell (2006).

SAF Stress evolution

SAF Stress evolution profiles

(Top) (a) Coulomb stress accumulation rate of the SAFS, evaluated at 1/2 of the locking depth, in MPa/100yrs.  (b) Calendar year 2007 Coulomb stress accumulation of the SAFS based on stress accumulation and contributions from 75 historical and prehistorical earthquake ruptures. (Bottom) Across-fault stress profiles based on historical and prehistorical earthquake activity of the SAFS.



2019 Ridgecrest Earthquake 

On July 4-5, 2019, the M6.4 and M7.1 Searles Valley and Ridgecrest earthquake sequence ruptured a geometrically complex 50 km long system of faults within the Eastern California Shear Zone (ECSZ), just north of the Garlock fault.  These conjugate events resulted in several meters of strike-slip and dip-slip along a fairly complex rupture, extending from the surface down to 15 km.  Coseismic geodetic observations reveal 500+ mm of horizontal surface slip and at least 35 mm of vertical uplift at near-field station P595, located 10 km from the rupture zone.   Some 70+ km away, smaller but still measurable subsidence and uplift motions (~8-12 mm) were also recorded, as predicted by far-field elastic dislocation theory.  Similarly, over the next several months to years, vertical velocity transients are anticipated, characteristic of postseismic viscoelastic relaxation of the lower crust and upper mantle.

A co-seismic slip source inversion of both events using GNSS and InSAR (Sentinel-1/ALOS-2) line-of-sight deformation data was computed (Xu et al., 2019). The modeled vertical coseismic deformation field of the Ridgecrest earthquake sequence reveals alternating quadrants of deformation (+/- 35 mm) that straddle the rupture and span a wide (~200 km) region of the ECSZ. 

Website:  https://topex.ucsd.edu/SV_7.1

Related Publications:

Xu, X., D.T. Sandwell, L. Ward, C. Milliner, B. Smith-Konter, P. Feng, and Y. Bock (2020), Surface deformation associated with fractures near the 2019 Ridgecrest earthquake sequence, accepted for publication in Science, Manuscript #abd1690.

Dawson, T. et al. (2020), Field-based observations of surface ruptures associated with the 2019 Ridgecrest earthquake sequence, submitted to BSSA.

Ponti, D. et al. (2020), Documentation of surface fault rupture and ground‐deformation features produced by the 4 and 5 July 2019 Mw 6.4 and Mw 7.1 Ridgecrest earthquake sequence, (2019),Seismol. Res. Lett., https://doi.org/10.1785/0220190322.

Xu, X., D.T. Sandwell, and B. Smith-Konter (2019), Co-seismic displacements and surface fractures from Sentinel-1 InSAR: 2019 Ridgecrest Earthquakes, Seismol. Res. Lett., https://doi.org/10.1785/0220190275.

Ridgecrest Insar

Ridgecrest GNSS vertical

(Top) Near-real time line-of-sight deformation data from both the Mw6.4 (July 4, 2019) and the Mw7.1(July 5, 2019) Ridgecrest earthquakes.  Both wrapped interferograms and line-of-sight (LOS) displacement maps were processed with open-source software GMTSAR.  (Bottom) Vertical coseismic GNSS measured displacements and modeled vertical displacement field resulting from 3-D surface displacement model of slip source inversion.





2018 Kilauea Deformation

The 2018 Kīlauea Volcano eruption and earthquake sequence provided an unprecedented opportunity to geodetically image volcanic and tectonic deformation in near-real time. Observed every three days from May-August 2018 by the Sentinel-1 satellite, the 2018 Kilauea event was a exceptional chance to rapidly obtain, process, and deliver interferometric synthetic aperture radar (InSAR) data and products to the scientific community for improved hazard forecasting and rapid assessment of remote regions to help direct emergency response and recovery efforts. Additionally, these data provided critical insights into the evolving deformation of the 2018 Kīlauea Volcano eruption from several sources:  (1) the April 30th collapse of Pu'u 'Ō'ō crater (2) the May 1st dike intrusion, propagation, and subsequent contraction of the lower East Rift Zone that extended from Puʻu ʻŌʻō to the Leilani Estates region (3) the continuous deflation of Kīlaueaʻs summit region as large volumes of magma were withdrawn (4) the sprawling deformation from the May 4th Mw6.9 Leilani Estates thrust earthquake along the south flank region.

With respect to the latter, current interpretation of geological and geophysical observations from Kīlaueaʻs south flank suggests that continuous creep, slow slip events, and major earthquakes are all occurring on the same fault plane. Integration of geodetic and seismic observations spanning the most recent sources of activity to those from several decades ago allow us to better understand earthquake phenomena, reconcile deformation rates, and quantify the processes that control fault stress and strain accumulation/transfer/release at Kīlauea.

Website and Data:    http://pgf.soest.hawaii.edu/Kilauea_insar/

Smith-Konter, B., L.Ward, L. Burkhard, X. Xu, and D.T. Sandwell, 2018 Kilauea eruption and Mw 6.9 Leilani Estates earthquake: Line of sight displacement revealed by Sentinel-1 interferometry, https://doi.org/10.6084/m9.figshare.6272219.

Smith-Konter, B., L.Ward, L. Burkhard, X. Xu, S. Slead, J. Foster, and D.T. Sandwell (2020), Geodetic imaging and hazard analysis of the 2018 Kilauea eruption, 2020 Goldschmidt Conference, invited plenary speaker.

Manuscript in preparation.



Kilauea Insar

Kilauea LOS

Near-real time line-of-sight deformation data of the 2018 Kilauea eruption from Sentinel-1.   InSAR data were rapidly processed with open source software GMTSAR. (Top) Wrapped interferogram map, where each fringe represents 2.8 cm of ground displacement toward (or away) from the satellite. (Bottom) Ascending unwrapped line-of-sight deformation maps, where red colors (positive) indicate motion toward the satellite (up or west) and blue colors (negative) indicate motion away from the satellite (down or east).





Tidal Stress & Faulting of Enceladus, Ganymede, and  Europa

This research is aimed at applying 3-D crustal deformation models to investigate the tectonic features found on the moons of Enceladus, Europa, Ganymede and more recently, Titan.  Our group investigates shear failure of fractures of icy moons driven by tidally induced stresses that are exerted on a satellite during its daily orbital cycle around its parent body.

Related publications:

Cameron, M., B. Smith-Konter, L. Burkhard, G. Collins, D. Patthoff, and R.T. Pappalardo (2020), Ganymede past and present:  How evolving eccentricity effects tidally-driven Coulomb failure, J Geophys. Res. Planets, doi:10.1029/2019JE005995.

Cameron, M., B. Smith-Konter, G. Collins, D. Patthoff, and R.T. Pappalardo (2019), Tidal stress modeling of Ganymede: Strike-slip tectonism and Coulomb failure, Icarus, 319, doi: 10.1016/j.icarus.2018.09.002.

Cameron, M., B. Smith-Konter, L. Burkhard, G. Collins, and R.T. Pappalardo (2018), Morphological mapping of Ganymede: Investigating the role of strike-slip tectonics in the evolution of terrain types, Icarus, , 315,  doi: 10.1016/j.icarus.2018.06.024.

Olgin, J., B. Smith-Konter, and R.L. Pappalardo (2011), The limits of Enceladusʻs ice shell thickness from tidally driven tiger stripe failure, Geophys. Res. Lett.,  38, doi:10.1029/2010GL044950.

Smith-Konter, B. and R.L. Pappalardo (2008), Tidally driven stress accumulation and shear failure of Enceladus's tiger stripes, Icarus, doi:10.1016/j.icarus.2008.07.005.

  View  animated models: 

                                  

(left)  SatStress model: Maximum tensile stress output as a function of orbital position at Enceladus's south pole.

(center)  Tiger stripe modeled fault stress accumulation as a function of orbital position.

(right) Tiger stripe modeled displacement fields (horizontal and vertical) as a function of orbital position.


Ganymede NSF stress model

Global failure predictions for strike-slip structures on Ganymede subject to diurnal and non-synchronous rotation tidal stress. (a) Normal stress fault orientation diagrams overlaying global imagery of Ganymede and maximum principal stress (σ1, MPa). Note regions of high compressive stresses near the equator. (b) Traction sense diagrams overlaying stress tensor component σθφ+φφ (MPa). (c) Coulomb failure orientation diagrams overlaying global imagery. Note regions of limited slip corresponding to high compressive stresses and low shear stresses. From Cameron et al. (2019).  

Enceladus stress displacement model
Modeled deformation of the tiger stripes from Enceladusʻs south pole. (left) Stress accumulation due to fault locking at periapse (Enceladusʻs closest orbital position to Saturn) and potential right-lateral fault displacement (right) due to a reduced compressive stresses at apoapse (Enceladusʻs orbital position at its farthest distance from Saturn).  From Smith-Konter and Pappalardo (2008).



3-D Elastic & Viscoelastic Crustal Deformation Modeling

Exploration of earthquake scenarios that span several thousand years, and deform over an equal number of kilometers, requires models that are three-dimensional, time-dependent, and computationally efficient. My Ph.D. thesis research was directed toward the development, verification, & application of a semi-analytical Fourier model describing the 3D response of both elastic and viscoelastic mediums to a distribution of body forces. Using Fourier analysis, the horizontal complexity of a given fault system has no effect on the speed of the computation; likewise, because the solution is analytic in time, no numerical time stepping is required. This approach allows for rapid computer model calculations that are over 20 times faster than previous methods (e.g., finite element methods). A single time-step for a mesh of 2048 by 2048 horizontal grid cells, containing over 400 fault patches, requires only 40 seconds of CPU time on a personal computer. Multiple time steps, including hundreds of years of earthquake history, can be computed in a matter of hours.

Model development involved extensive testing against analytic solutions including: 2-D analytic tests of a homogeneous elastic half-space [Weertman, 1964], a layered elastic half-space [Rybicki, 1971], non-surface observation planes [Savage and Lisowski, 1993], and a layered viscoelastic half-space [Nur and Mavko , 1977]; 2-D analytic Boussinesq tests for the point load solution [Love, 1944] and the thin-plate flexure solution [Le Pichon et al., 1973]; a 3-D elastic half space   [Okada, 1985, 1992].

Related Publications:

Sandwell, D.T. and B. Smith-Konter (2018), Maxwell:  A semi-analytic 4-D code for earthquake cycle modeling of transform fault systems, Computers and Geosciences, doi: 10.1016/j.cageo.2017.737.

Smith, B.R. and D.T. Sandwell, A 3-D semi-analytic viscoelastic model for time-dependent analyses of the earthquake cycle, J. Geophys. Res., doi:10.1029/2004JB003185, 2004.

Smith, B. R. and D. T. Sandwell, Coulomb stress along the San Andreas Fault System, J. Geophys. Res., 108, doi:10.1029/2002JB002136, 2003.

Fourier model 

View animated models:

 3D Deformation movie __ __stress evolution movie

                      Example 3D Velocity Model ___________  Example Coulomb Stress Model




GPS & InSAR Applications 

Space geodetic techniques, such as GPS and InSAR, provide valuable data that offer a detailed synoptic picture of the strain accumulation along Earth's plate boundaries. However, modeling of these data is critical in order to determine the corresponding tectonic stress and rheologic parameters.   Accurate models must incorporate time-dependent interactions among complex 3-D fault systems. Using the 3D Fourier model described above, along with 1000+ GPS-derived horizontal velocity measurements, calculations of both secular and episodic deformation and stress due to plate boundary forces are feasible.

Likewise, InSAR data can also be efficiently investigated using 3D crustal deformation models. For example, ascending and descending interferograms derived from ERS satellites have been used to estimate surface slip and fault parameters along the Hector Mine earthquake rupture [Sandwell et al., 2002].   Large-scale synthetic interferograms can also be produced for the purpose of integrating GPS and InSAR data to provide both high spatial and high temporal resolution at the plate boundary.

Related Publications:

Tong,X., B. Smith-Konter, and D.T. Sandwell, Is there a discrepancy between geological and geodetic slip rates along the San Andreas Fault System? (2014), J. Geophys. Res., doi:10.1029/2013JB010765.

Tong, X., D.T. Sandwell, and B. Smith-Konter (2013), High-resolution interseismic velocity data along the San Andreas Fault System, J. Geophys. Res., 118, doi:10.1029/2012JB009442.

Smith-Konter, B., D. Sandwell, and M. Wei (2010), Integrating GPS and InSAR to resolve stressing rates of the SAF System, EarthScope inSights Newsletter, Summer 2010.

Wei, M., D. Sandwell, and Smith-Konter, B., Optimal combination of InSAR and GPS for measuring interseismic crustal deformation, J. Adv. in Space Res., doi: 10.1016/j.asr.2010.03.013, 2010.

Wdowinski, S., B. Smith-Konter, Y. Bock, and D.T. Sandwell (2007), Diffuse interseismic deformation across the Pacific-North America plate boundary, Geology, doi:10.1130/G2938A.1.

Sandwell, D. T., L. Sichiox, and B. R. Smith, The 1999 Hector Mine Earthquake: Vector near-field displacements from ERS InSAR, Bull. Seismo. Soc. Am., 92, 1341-1354, 2002.




SAF deformation GPS

Fault-parallel velocity model of the San Andreas Fault System. (b) Modeled velocity profiles acquired across the center of each fault corridor with GPS velocities projected onto profiles for visual comparison.

SAF strain rate

Strain rate of the San Andreas Fault System from a geodetically constrained analytical crustal deformation model. Deep slip occurs on 41 fault segments, where geologic slip rate is applied and locking depth is varied along each fault segment to best fit the GPS data. Inset: Velocity model profile (black line), GPS data (gray circles), and strain rate across the Imperial fault.



Home Earth@UH SOEST@UH