Seismic Anisotropy Beneath the Pamir and the Hindu Kush: Evidence for Contributions From Crust, Mantle Lithosphere, and Asthenosphere

Abstract

We use local and teleseismic earthquakes to analyze shear wave splitting within the Pamir‐Hindu Kush region, north of the western syntaxis of the India‐Asia collision zone. These two data sets allowed us to map the distribution of azimuthal anisotropy, to put constraints on the depth range where it is accumulated, and to deduce characteristics of ongoing deformation. From 1,073 SKS (core‐mantle refracted phases) measurements at 107 stations, we derived time delays of 0.7–2.25 s and dominantly ENE‐WSW oriented fast polarization directions. Fast polarization directions only deviate adjacent to the subducting slabs and major strike‐slip faults, aligning parallel to these structures. From 461 direct S measurements along a transect perpendicular to the Pamir seismic zone, we obtain fast directions parallel to those from SKS measurements but smaller delay times (average 0.4 s), which vary depending on depth. Time delays exhibit 0.1–0.3 s crustal contribution and increase to 0.8 s in a narrow domain coinciding with the inferred subcrustal contact of the two colliding plates. We find measurements from the same event‐station paths at different filter frequencies to be frequency‐independent, allowing a comparison with SKS results along the studied profile. The smaller average time delays of local events imply that the crust and uppermost mantle only make a minor contribution to the SKS splitting. Thus, the coherent fast direction pattern suggests a strain field dominated by the indentation of India and the escape of sublithospheric material north of the indenter. Crustal anisotropy is likely also controlled by this regional deformation pattern with locally highest strain rates closest to the continental subduction front.

Interaction of the Indian and Asian Plates Under the Pamir and Hindu‐Kush Regions: Insights From 3‐D Shear Wave Velocity and Anisotropic Structures

“…Two opposing subduction slabs (i.e., the Indian and Asian slabs) may have interacted under the Pamir, inducing horizontal mantle flow squeezed by two strong slabs outward from the Pamir to its flank (Figure 11a), which is also supported by the strong positive radial anisotropy at the depths of Moho-205 km (Figures 6c-6i) in the Pamir arc. Horizontal mantle flow (in lithospheric mantle and asthenosphere) could result in deformed fabrics with a NE-SW extension in an arc shape (Peng et al, 2020), consistent with the observations of ENE-WSW trending azimuthal anisotropy from shear wave splitting (Kufner et al, 2018) and Pn wave tomography (Zhou & Lei, 2015;Lü et al, 2017) in an arc shape in the Pamir region. We also notice that deep earthquakes with focal depths > 100 km widely locate at the boundary of two high velocity anomaly.…”

“…As shown in the cross sections (Figures 8 and 9), the high velocity anomaly shows as a horizontal plate that prostrates beneath the South Pamir with its deep interface down to~180 km depth, consistent with the observations from receiver function (Kumar et al, 2005) and body wave tomography (Sippl, Schurr, Yuan, Figure 6. (a-i) Map of radial anisotropy models; pink lines indicate the results of SKS splitting (Kufner et al, 2018); black dots denote seismicity at corresponding depths; panel (i) show the location of cross sections A-D ( Figure 7) of radial anisotropy models.…”

The Crust in the Pamir: Insights From Receiver Functions

“…The Moho shallows from 39 to 38.5°N and deepens again to 38°N. Strong crustal deformation has been inferred in this region from seismic anisotropy (Kufner, Eken, et al, ). The thinning of the Pamir crust at 38.5°N can be explained by the buckling effect due to the delamination and rollback of the cratonic Asian lithosphere beneath the thick crust and lithosphere of the Pamir.…”

SKS Splitting Measurements in NE China: New Insights Into the Wudalianchi Intraplate Volcanism and Mantle Dynamics

“…However, the obtained results are usually inconsistent with each other, probably due to differences in the analysis method, parameter selection, and data set used. Kufner et al (2018) pointed out that the splitting time, δt, is sensitive to the averaging method adopted.…”