Refining the shallow slip deficit

Abstract

S U M M A R YGeodetic slip inversions for three major (M w > 7) strike-slip earthquakes (1992( Landers, 1999 Hector Mine and 2010 El Mayor-Cucapah) show a 15-60 per cent reduction in slip near the surface (depth < 2 km) relative to the slip at deeper depths (4-6 km). This significant difference between surface coseismic slip and slip at depth has been termed the shallow slip deficit (SSD). The large magnitude of this deficit has been an enigma since it cannot be explained by shallow creep during the interseismic period or by triggered slip from nearby earthquakes. One potential explanation for the SSD is that the previous geodetic inversions lack data coverage close to surface rupture such that the shallow portions of the slip models are poorly resolved and generally underestimated. In this study, we improve the static coseismic slip inversion for these three earthquakes, especially at shallow depths, by: (1) including data capturing the near-fault deformation from optical imagery and SAR azimuth offsets; (2) refining the interferometric synthetic aperture radar processing with non-boxcar phase filtering, modeldependent range corrections, more complete phase unwrapping by SNAPHU (Statistical Nonlinear Approach for Phase Unwrapping) assuming a maximum discontinuity and an onfault correlation mask; (3) using more detailed, geologically constrained fault geometries and (4) incorporating additional campaign global positioning system (GPS) data. The refined slip models result in much smaller SSDs of 3-19 per cent. We suspect that the remaining minor SSD for these earthquakes likely reflects a combination of our elastic model's inability to fully account for near-surface deformation, which will render our estimates of shallow slip minima, and potentially small amounts of interseismic fault creep or triggered slip, which could 'make up' a small percentages of the coseismic SSD during the interseismic period. Our results indicate that it is imperative that slip inversions include accurate measurements of near-fault surface deformation to reliably constrain spatial patterns of slip during major strike-slip earthquakes.

Revisiting the 1992 Landers earthquake: a Bayesian exploration of co-seismic slip and off-fault damage

“…Most of the slip concentrates along the central and northern parts of the rupture, with a peak amplitude of ∼11 m. These features are to first order comparable to previous results, although published models have lower peak slip amplitudes (e.g. Cohee & Beroza 1994;Fialko 2004b;Xu et al 2016). This difference is probably due to smoothing imposed in previous studies that decreases the maximum slip amplitude.…”

“…Murray et al 1993;Cohee & Beroza 1994;Freymueller et al 1994;Hudnut et al 1994;Wald & Heaton 1994;Cotton & Campillo 1995;Fialko 2004b;Xu et al 2016). Common patterns emerge in the inferred slip distributions including the fact that most of the slip occurred in the central section of the rupture (i.e.…”

“…Inelasticity would bias slip models where observations at short distances are modelled assuming elastic Green's functions. An apparent shallow slip deficit could also be caused by smoothing constraints and sparseness of near-fault data (Simons et al 2002;Xu et al 2016). Finally, unaccounted heterogeneities in the crust elastic properties can also result in a biased slip distribution at depth (Barbot et al 2008).…”

Landers 1992 "reloaded": Integrative dynamic earthquake rupture modeling

“…While Xu et al [2016] argue that the majority of inferred SSD is a result of poor resolution of near-fault surface data in slip inversions, it is often attributed to coseismically occurring plastic deformation at shallow depths [e.g., Kaneko and Fialko, 2011;Milliner et al, 2015]. Numerical models show that shallow slip is already reduced by 18.6 % in simulations with purely elastic material properties [supplemental material of Roten et al, 2017].…”

“…The wealth of observational data has been analyzed to shed light on the slip distribution from inversion of seismological and geodetic data [e.g., Wald and Heaton, 1994;Cohee and Beroza, 1994;Freymueller et al, 1994;Cotton and Campillo, 1995;Fialko, 2004a;Xu et al, 2016] and to constrain rupture dynamics [e.g. Peyrat et al, 2001;Aochi and Fukuyama, 2002;Fliss et al, 2005;Heinecke et al, 2014;Wollherr et al, 2018].…”