Bayesian inversion for modeling 3D density structures in the eastern margin of Bayan Har block and its tectonic implications

Abstract

Recently, the eastern margin of the Tibetan plateau has experienced three moderate earthquakes. Deep crustal structure is a critical factor for understanding the seismotectonic environment and deformations in this region. While several multidisciplinary geophysical approaches have been employed to develop crustal structure models for this area, substantial inconsistencies still persist in the results due to the intricate structural properties of crust. In this study, we introduce a novel approach to construct a three-dimensional crustal model with assimilated density structure (MADS) at a resolution of 0.2° ×0.2°×5 km. This model is built by integrating data from various source, including multi-source gravity anomalies and diverse available crustal structure reference models. We employ a model-assimilated gravity inversion process with Bayesian parameter optimization. Firstly, we combine the terrestrial gravity profiles dataset with published global gravity field models to create a dataset rich in reliable high-frequency anomaly information. Secondly, we incorporate three reference models derived from different seismological methods as prior constraints for our model. These models encompass seismic tomography, surface wave dispersion and receiver function data. We optimize the hyper-parameters of these constraints using the Bayesian criterion. The results demonstrate that the MADS not only captures significant changes in the crustal density but also discerns subtle variations in the upper and middle crust, thereby providing detailed insights into the morphologies of major faults. For instance, the central section of the Longmenshan fault is revealed as a high-angle deep thrust feature, while the frontal section of the Longmenshan fault appears as a low-angle mid-deep thrust feature, and the Xianshuihe fault exhibits a vertical deep subduction feature. Additionally, our findings indicate a correlation between the locations of moderate-to-large earthquakes in this region and the high density-gradient zones or asperities with high density within MADS. We believe that the insights into density characteristics offered by the new MADS model can shed light on the study of asperities associated with recent moderate earthquakes and enhance our understanding of deformation in this region.