Crustal thickness and Vp/Vs variation beneath continental China revealed by receiver function analysis

Abstract

SUMMARY Using data from 3837 seismic stations deployed in or around continental China, we construct high-resolution models of crustal thickness (H) and seismic compressional and shear velocity ratio (Vp/Vs or κ) in continental China by analysis of 150 543 receiver functions. We group the receiver functions in cells with a spatial resolution of 0.25° × 0.25° in the North–South China Seismic Belt and parts of the North China Craton, and of 0.5° × 0.5° in other regions, classify the receiver functions based on their characteristics, and develop a modified H–κ stacking method to construct models in the regions where the receiver functions are significantly affected by sedimentary basins and by Moho architecture. The inferred crustal thickness model displays an eastward thinning trend from the thickest crust (>80 km) beneath the Qiangtang Block to the thinnest crust (<26 km) beneath the southern part of the Cathaysia Block. Crustal thickness is 26–50 km in several major basins and 26–55 km in the Precambrian cratonic blocks. The inferred Vp/Vs model in the crystalline crust displays moderate-to-high values (1.75–1.85) in the southeastern margin of the Tibetan Plateau, the Tengchong volcanic field, the Emeishan large igneous province, the north-central areas of the Bohaiwan and Songliao basins, the western margin of the Taikang Hefei Basin and the southeastern margin of the Cathaysia Block. Lower values (≤1.72) characterize the major regions of the Cathaysia Block and the Jiangnan Orogenic Belt, and the hinterlands of the Ordos Block and Sichuan Basin. We discuss possible tectonic processes, secular crustal evolution and crustal compositions that are consistent with our inferred crustal thickness and Vp/Vs structure in continental China. This study establishes a framework of seismic data sharing for future studies in the seismological community in one of the first steps of developing a China Seismological Reference Model.