Spatiotemporal Variation of Mantle Viscosity and the Presence of Cratonic Mantle Inferred From 8 Years of Postseismic Deformation Following the 2010 Maule, Chile, Earthquake

Abstract

Postseismic displacements following great subduction earthquakes show significant long‐wavelength and time‐dependent patterns caused primarily by transient viscoelastic relaxation processes occurring broadly at depth. However, the Earth's viscosity structure and time‐dependent variations are still poorly understood, especially in the years immediately following a great earthquake. Here we investigate the spatiotemporal variation of mantle viscosity proximal and distal to the southern Andes using 8 years of continuous high‐resolution GPS observations following the 2010 Mw 8.8 Maule earthquake in south Central Chile. We remove the potential influences of relocking and afterslip on far‐field GPS displacements and estimate viscosities that can explain the 3‐D displacements. The optimal viscosity structure exhibits a low‐viscosity (~1018Pa s) mantle beneath the Andean volcanic arc and high‐viscosity (>1022Pa s) cratonic mantle, indicating a dependence of transient viscosity on temperature. Comparisons of the viscosity distributions at different times show that mantle viscosities increase with time throughout the study region. Viscosity increase is generally fastest in the mantle wedge beneath the Andes and slows down with increasing distance from the source region of the Maule earthquake. Such temporal viscosity evolution may indicate a stress dependence of the viscosity proximal to the rupture zone, while regions east of the Andes act as a relatively rigid body (i.e., cratonic mantle) with much higher viscosity. Our results thus suggest that both temperature structure and stress state contribute to spatiotemporal variations of the mantle viscosity. Heterogeneous spatiotemporal variations of viscosity seem to control the expansion and duration of the postseismic deformation and therefore the postseismic stress evolution.

Postseismic Deformation due to the 2012 Mw 7.8 Haida Gwaii and 2013 Mw 7.5 Craig Earthquakes and its Implications for Regional Rheological Structure

“…In addition to a Burgers body, a power law rheology has also been used to describe the temporal change of postseismic viscosity, which allows for a time‐dependent continuous increase of viscosity (Agata et al., 2019; Freed & Bürgmann, 2004; Kogan et al., 2013; Li et al., 2018; Qiu et al., 2018). By comparing the viscosity distributions at different times and regions, Li et al.…”

“…By comparing the viscosity distributions at different times and regions, Li et al. (2018) found that the viscosities following the 2010 Maule earthquake increased with time and correlated with the temperature structure and stress state. Based on the power law rheology, Agata et al.…”

“…In addition to a Burgers body, a power law rheology has also been used to describe the temporal change of postseismic viscosity, which allows for a time-dependent continuous increase of viscosity (Agata et al, 2019;Freed & Bürgmann, 2004;Kogan et al, 2013;Li et al, 2018;Qiu et al, 2018). By comparing the viscosity distributions at different times and regions, Li et al (2018) found that the viscosities following the 2010 Maule earthquake increased with time and correlated with the temperature structure and stress state. Based on the power law rheology, Agata et al (2019) inferred that the transient viscosity increased quickly following the 2011 Tohoku earthquake, but the steady viscosity changed slowly.…”

Impacts of Topographic Relief and Crustal Heterogeneity on Coseismic Deformation and Inversions for Fault Geometry and Slip: A Case Study of the 2015 Gorkha Earthquake in the Central Himalayan Arc

“…In the past decades, space‐based geodetic systems, in particular Global Positioning System (GPS) and interferometric synthetic aperture radar (InSAR), have revolutionized our ability to monitor actively deforming areas with unprecedented spatial and temporal resolutions, revealing a wide spectrum of deformation processes that related to active tectonics on Earth (Bürgmann & Thatcher, 2013). Modeling of these geodetic observations has provided further insights into the fault kinematics and rheological structure at large‐scale fault systems in the different stages of earthquake cycle (e.g., Arnadóttir & Segall, 1994; Bürgmann & Dresen, 2008; Fialko, 2006; Freed et al., 2017; Hearn & Bürgmann, 2005; Itoh et al., 2019; Li et al., 2015; Li, Bedford et al., 2018; Pollitz, 2015; Qiu et al., 2018; Sato et al., 2010; T. Sun & Wang, 2015; K. Wang et al., 2012; Zhao et al., 2017). For the coseismic stage, surface deformation has been used to invert for the fault geometry (including its depth, strike, and dip angles) and slip distribution (i.e., earthquake source) of earthquakes at depth (e.g., Arnadóttir & Segall, 1994; Clarke et al., 1997; Reilinger et al., 2000; Simons et al., 2002).…”

An Approximate Method to Simulate Post-Seismic Deformations in a Realistic Earth Model

“…An entire earthquake process may contain three major phases: the inter-seismic accumulation, the co-seismic transient deformation, and the long-term post-seismic adjustment. The viscoelastic relaxation deformation, as a major mechanism of the post-seismic phase, can be captured using modern geodetic technologies for megathrust earthquakes (e.g., Wang et al 2012;Sun et al 2014;Li et al 2018;Qiu et al 2019;Agata et al 2019). To explain the multiple observations and investigate the physical mechanisms, accurate modeling for such processes is a necessity and attractive to geophysicists and geodesists.…”