联合slipBERI与D-InSAR技术的青海省玛多县地震形变场提取与模拟

针对2021年5月22日青海玛多县Ms7.4地震震区形变信息、形变特征以及滑动断裂特性的提取与模拟等问题，获取了玛多县地震区的Sentinel-1A影像，采用双轨差分干涉法，并优化各项参数，提取出同震形变场，利用slipBERI(slip from Bayesian Regularized Inversion)方法对断层的几何参数及形变场进行反演和模拟。结果表明：玛多地震同震形变场的形状近似于一个椭圆，断层整体呈西北-东南走向，其上部为沉降区，下部为隆升区，最大LOS(line of sight,视线向)形变分别为0.65m和0.81m。地震形变场的运动主要以东西方向的水平运动为主，并伴有明显的左旋走滑，断层上下方相对视线向运动可达1.50m，表明此次地震的地表破裂有明显的错位移动。通过分析形变信息和地表破裂特征，可以判断该破裂带位于巴颜喀拉块体，为昆仑山口-江口断裂，反演结果与观测结果相符，这表明观测结果较可靠。

Extraction and Simulation of Earthquake Deformation Field in Maduo County, Qinghai Province Combined with slipBERI and D-InSAR Technology

Aiming at the extraction and simulation of the deformation information, deformation characteristics and sliding fault characteristics of the Ms7.4 earthquake that occurred in Maduo County, Qinghai on May 22, 2021. In this contribution, the Sentinel-1A images of the Maduo County earthquake region were obtained, and the seismic deformation field was extracted by using the dual-track differential interferometry and optimizing the parameters. The slipBERI (slip from Bayesian Regularized Inversion) method is used to invert and simulate the geometrical parameters and deformation field of the fault. The results show that the appearance of the co-seismic deformation field of this earthquake is approximately an ellipse, and the whole fault shows a northwest-southeast trend, with a subsidence area above and a uplift area below. The maximum LOS (line of sight) deformation is 0.65m and 0.81m respectively. The seismic deformation field is dominated by horizontal movement in the east-west direction, showing obvious left-handed strike-slip characteristics. The relative LOS movement on both sides of the fault can reach 1.50m, which reflects the obvious dislocation displacement of the surface rupture of the earthquake. By analyzing deformation information and surface fracture characteristics, it can be judged that the rupture zone which is located in the Bayan Har block is the Kunlun Pass-Jiangkou fault. The inversion results are consistent with the observations, which indicates that the observations are more reliable.