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Intraplate Seismicity in Central and Southeastern Brazil Due to Lithospheric and Upper-Mantle Heterogeneities: A Geodynamic Perspective
Abstract
Intraplate seismic activity in stable cratons often shows little correlation with surface geological features. While major extensional structures, like aborted continental rifts, can serve as zones of weakness, geology-based models often fail to explain variations in seismic activity in continental regions away from active tectonic boundaries. In central and southeastern Brazil, seismic activity is notably not uniform, with certain areas experiencing higher levels of activity and they show almost no correlation with the main geological provinces. Using a series of 3D numerical models, this study aims to understand the stress field in this region by examining the contributions from crustal and upper-mantle heterogeneities, as revealed through seismic tomography. A crustal seismic velocity model was used to determine the effects of crustal thickness and density variation on the observed intraplate seismicity. Additionally, upper-mantle seismic velocity anomalies from a regional tomography model were converted to a temperature field, which provided insights into lithospheric thickness variations, and density anomalies. . This density structure combined with rheological modelling show evidences of presence of neutrally buoyant plume and remnants of subducting slabs beneath Brazil craton. These heterogeneities in the crust and upper mantle influenced the buoyancy forces and rheology in our models. The model, incorporating upper-mantle thermal anomalies and approximately 30 MPa of east-west compression, produced a stress field that aligns with the observed seismicity in Brazil. We also find that distribution of gravitational potential energy (GPE) and crustal thickness gradient have a positive correlation with the observed seismicity. Our model findings show the uncompensated nature of the crustal blocks in the study area which can be an underlying reason for the seismicity. Previous studies on gravity anomaly and elastic thickness of the lithosphere match with our numerical model results. Our results suggest that the stress perturbations arising from mantle flow due to upper-mantle heterogeneities , combined with gravitational potential energy distribution and crustal thickness gradients, can better explain the intraplate seismicity in this region.
Keywords: Intraplate seismicity, Stress concentrations, Lithospheric and upper-mantle heterogeneities, 3D numerical models, GPE, Crustal thickness gradient, Isostatic compensation
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Computations have helped elucidate the dynamics of Earth's mantle for several decades already. The numerical methods that underlie these simulations have greatly evolved within this time span, and today include dynamically changing and adaptively refined meshes, sophisticated and efficient solvers, and parallelization to large clusters of computers. At the same time, many of these methods -- discussed in detail in a previous paper in this series -- were developed and tested primarily using model problems that lack many of the complexities that are common to the realistic models our community wants to solve today. With several years of experience solving complex and realistic models, we here revisit some of the algorithm designs of the earlier paper and discuss the incorporation of more complex physics. In particular, we re-consider time stepping and mesh refinement algorithms, evaluate approaches to incorporate compressibility, and discuss dealing with strongly varying material coefficients, latent heat, and how to track chemical compositions and heterogeneities. Taken together and implemented in a high-performance, massively parallel code, the techniques discussed in this paper then allow for high resolution, 3d, compressible, global mantle convection simulations with phase transitions, strongly temperature dependent viscosity and realistic material properties based on mineral physics data.
Mid-plate South America remains one of the least-studied regions of intraplate seismicity. Little is known about the origin and controlling factors that make this area the least seismically active intraplate region in the world. We analysed the distribution of intraplate seismicity and its correlation with several geophysical lithospheric parameters in an attempt to establish which factors might promote or inhibit the occurrence of intraplate earthquakes. We found that above-average seismicity occurs mostly in Neoproterozoic fold belts, associated with areas having a positive gravity anomaly, lower elastic thickness, higher heat flow, thinned crust and a negative S-wave anomaly at 100 km depth (associated with non-cratonic crust). Cratonic areas with a higher elastic thickness and lower heat flow are associated with low rates of seismicity. Our study suggests that the most important controlling factors are elastic thickness and heat flow. We propose that earthquake-prone areas with these favourable conditions correspond to regions of weakened lithosphere, where most of the regional lithospheric stresses are supported by the overlying brittle upper crust. These areas act as local concentrators of the regional compressional stress field, with the stress build-up then leading to the occurrence of intraplate seismicity.
Our new 1-by-1 degree global crustal model, CRUST1.0, was introduced
last year and serves as starting model in a comprehensive effort to
compile a global model of Earth's crust and lithosphere, LITHO1.0
(Pasyanos et al., 2012). The Moho depth in CRUST1.0 is based on 1-degree
averages of a recently updated database of crustal thickness data from
active source seismic studies as well as from receiver function studies.
In areas where such constraints are still missing, for example in
Antarctica, crustal thicknesses are estimated using gravity constraints.
The compilation of the new crustal model initially followed the
philosophy of the widely used crustal model CRUST2.0 (Bassin et al.,
2000; http://igppweb.ucsd.edu/~gabi/crust2.html) to assign elastic
properties in the crystalline crust according to basement age or
tectonic setting (loosely following an updated map by Artemieva and
Mooney (2001; http://www.lithosphere.info). For cells with no local
seismic or gravity constraints, statistical averages of crustal
properties, including crustal thickness, were extrapolated. However, in
places with constraints the depth to basement and mantle are given
explicitly and no longer assigned by crustal type. This allows for much
smaller errors in both. In each 1-degree cell, boundary depth,
compressional and shear velocity as well as density is given for 8
layers: water, ice, 3 sediment layers and upper, middle and lower
crystalline crust. Topography, bathymetry and ice cover are taken from
ETOPO1. The sediment cover is based on our sediment model (Laske and
Masters, 1997; http://igppweb.ucsd.edu/~sediment.html), with some
near-coastal updates. In an initial step toward LITHO1.0, the model is
then validated against new global surface wave disperison maps and
adjusted in areas of extreme misfit. This poster presents the next
validation step: compare the new Moho depths with in-situ active source
and receiver function results. We also present comparisons with
CRUST2.0. CRUST1.0 is available for download. References:
Pasyanos, M.E., Masters, G., Laske, G. and Ma, Z., LITHO1.0 - An Updated
Crust and Lithospheric Model of the Earth Developed Using Multiple Data
Constraints, Abstract T11D-09 presented at 2012 Fall Meeting, AGU, San
Francisco, Calif., 3-7 Dec, 2012. Artemieva, I.M. and Mooney, W.D.,
Thermal thickness and evolution of Precambrian lithosphere: A global
study, J. Geophys. Res., 106, 16,387-16,414, 2001. Bassin, C., Laske,
G. and Masters, G., The Current Limits of Resolution for Surface Wave
Tomography in North America, EOS Trans AGU, 81, F897, 2000. Laske, G.
and Masters, G., A Global Digital Map of Sediment Thickness, EOS Trans.
AGU, 78, F483, 1997. URL: http://igppweb.ucsd.edu/~gabi/crust1.html
Modelling the lithospheric stress field has proved to be an efficient means of determining the role of lithospheric versus sublithospheric buoyancies and also of constraining the driving forces behind plate tectonics. Both these sources of buoyancies are important in generating the lithospheric stress field. However, these sources and the contribution that they make are dependent on a number of variables, such as the role of lateral strength variation in the lithosphere, the reference level for computing the gravitational potential energy per unit area (GPE) of the lithosphere, and even the definition of deviatoric stress. For the mantle contribution, much depends on the mantle convection model, including the role of lateral and radial viscosity variations, the spatial distribution of density buoyancies, and the resolution of the convection model. GPE differences are influenced by both lithosphere density buoyancies and by radial basal tractions that produce dynamic topography. The global lithospheric stress field can thus be divided into (1) stresses associated with GPE differences (including the contribution from radial basal tractions) and (2) stresses associated with the contribution of horizontal basal tractions. In this paper, we investigate only the contribution of GPE differences, both with and without the inferred contribution of radial basal tractions. We use the Crust 2.0 model to compute GPE values and show that these GPE differences are not sufficient alone to match all the directions and relative magnitudes of principal strain rate axes, as inferred from the comparison of our depth integrated deviatoric stress tensor field with the velocity gradient tensor field within the Earth's plate boundary zones. We argue that GPE differences calibrate the absolute magnitudes of depth integrated deviatoric stresses within the lithosphere; shortcomings of this contribution in matching the stress indicators within the plate boundary zones can be corrected by considering the contribution from horizontal tractions associated with density buoyancy driven mantle convection. Deviatoric stress magnitudes arising from GPE differences are in the range of 1-4 TN m-1, a part of which is contributed by dynamic topography. The EGM96 geoid data set is also used as a rough proxy for GPE values in the lithosphere. However, GPE differences from the geoid fail to yield depth integrated deviatoric stresses that can provide a good match to the deformation indicators. GPE values inferred from the geoid have significant shortcomings when used on a global scale due to the role of dynamically support of topography. Another important factor in estimating the depth integrated deviatoric stresses is the use of the correct level of reference in calculating GPE. We also elucidate the importance of understanding the reference pressure for calculating deviatoric stress and show that overestimates of deviatoric stress may result from either simplified 2-D approximations of the thin sheet equations or the assumption that the mean stress is equal to the vertical stress.