利用连续GPS观测资料研究川西南地区长周期慢滑移事件

With the unprecedented development of GPS (Global Positioning System) seismology，using continuous GPS observations to detect long-term slow slip events(SSE) become a reality and it is widely used in subduction zones with strong tectonic movement. At Sichuan area, strong earthquakes cluster and fault geometry present intricately, as well as the crustal stress-strain accumulate. Especially in southwestern Sichuan area, the potential risks of strong earthquakes still exist. Therefore, it is necessary to investigate the SSEs associated to strong earthquakes. In order to investigate the SSEs contain in ground deformation signals, the research carried out mainly at the following three parts. 1) By resolving and analyzing the continuous GPS observations, obtain the coordinate time series of continuous operating reference stations in the area. Then pre-process the observations, remove the affection caused by surface mass loading, and extract the common mode errors to optimize the coordinate time series. 2) In order to recognize and extract the SSEs signals contain in the coordinate time series, model the series and access the noise characteristics to estimate the model parameters, then compare parameters at different time windows and different stations to obtain abnormal coordinate time series, and extract the SSEs signals from the abnormal phenomenon. 3) Using PCAIM (Principal Component Analysis based.Inversion Method, PCAIM) model to inverse the coordinate time series of SSEs signals, obtain the areas, magnitude of SSEs, and also the motion form of the crustal at various depths. The investigation can help provide a method of recognizing and extracting SSEs signals from abnormal coordinate time series of continuous GPS stations, and provide valuable displacements constraints for the geometry and evolution of the blocks and faults during SSEs. Furthermore, it can help understand the spatial and temporal evolution rule of strong earthquakes.

随着GPS地震学的快速发展，利用连续GPS观测资料探测长周期慢滑移事件已成为可能，并广泛运用于构造运动强的俯冲带。在强震丛集的四川区域，断裂带错综复杂，地壳应力积累程度较高。尤其在四川西南部，仍存在强震的潜在危险性，研究该区域与强震相关的慢滑移事件极为必要。项目对慢滑移事件的研究主要从如下三方面展开：1）解算分析高精度连续观测资料，获取高精度连续运行参考站的坐标时序。经数据预处理和数据优化，扣除与慢滑移事件不相关的信息，如地表质量负荷和共模噪声等；2）对坐标时序建模，分析误差项的噪声特性并求取模型参数。对比分析不同时间尺度、不同测站的运动表征，以异常运动现象为突破口，识别与提取慢滑移事件；3）建模和反演慢滑移事件发生的区域面积、强度信息，以及不同深度地壳的运动形态。该研究能提出一种慢滑移信息的捕捉方法，为块体、断层的几何形态与演化过程提供观测约束，辅助认识强震的时空演变规律。

GNSS坐标时序模型中需分离稳态速度场，采用对数或指数函数模型精确估计震后弛豫项，并去除季节性周期项影响，从包含噪声的残差时序中探测出慢滑移事件。时序模型中各项因素的影响，在滑移反演时通过主成份分析方法可在一定程度上予以分离，但无法分离滑移量较小的慢滑移事件。以日本Boso区域慢滑移事件为例，采取时序建模和主成分反演方法相结合，分析速度场、震后弛豫项、季节性周期项对慢滑移事件探测的影响；模拟缩放实际慢滑移量，分析不同大小慢滑移事件探测的难度。另外，采用加权非线性最小二乘估计震后对数弛豫时间，更准确的提取震后对数弛豫项，从而能分析震后弛豫项对测站位移的独立物理贡献，并为震后余滑、黏滞性松弛效应、慢滑移等现象的分析提供参考。以日本2009-2019年GPS坐标时序为例，估计2011年Mw9.0地震震后对数弛豫时间，发现不同站点的对数弛豫时间与其震中距关系显著，且服从高斯分布。据此，构建高斯函数加常数模型，可由震中距概略估计震后对数弛豫时间。高斯分布曲线的峰值、峰值位置、半宽度信息、最低位置分别为3.5年、0km、262km、0.5年，由此得出震后对数弛豫项影响时间大于0.5年的站点主要集中在震中距约524km范围内。震后弛豫效应区域分布的差异性显著，对数弛豫时间越长的区域，弛豫项水平位移表征越大，其中存在两个平均弛豫时间2.5年的中心区域，与震后余滑的中心区域及时间相吻合。GNSS坐标时序精细化建模,从而提取并反演慢滑移事件，有助于深化认识断层动力学发展规律，并为地震可能发生的时间段和危险区域提供参考。