GPS监测慢滑移事件的NIF反演及时空特征分析

NIF inversion and spatiotemporal analysis of GPS monitoring slow slip events

  • 摘要: 研究利用全球卫星定位系统(Global positioning system, GPS)坐标时序与网络反演滤波(Networkinversion filter, NIF)方法反演慢滑移事件,分析慢滑移的时空特征及演化规律,探讨慢滑移事件与地震发生的关联性。首先,对GPS连续坐标时序构建标准线性轨迹模型(Standard linear trajectory model,SLTM),剔除粗差并修复阶跃项,去除震前常数项和稳态速度项,去除年和半年周期季节项,提取慢滑移坐标时序;然后,利用NIF生成断层格网模型,引入弹性格林函数描述断层滑移与地表位移的关系,从而结合GPS慢滑移坐标时序反演断层格网上的滑移矢量及地表位移矢量;最后,统计慢滑移发生前后区域地震发生的大小及频率,分析慢滑移与地震发生可能存在的关系。以日本房总半岛2018年慢滑移事件为例展开研究,结果表明:慢滑移活跃期为年积日156至169;最大累积滑移量约11.3厘米,最大滑移率约2.7厘米/天;滑移中心区域为房总半岛东南部(34.8°N~35.6°N, 140.2°E~140.9°E),略微向南传播,滑移深度由深(约23km)及浅(约15km);慢滑移事件发生期间区域地震发生频率明显增大,之后几个月内地震发生频率逐渐恢复至平常,从房总半岛慢滑移动态演化中可判识潜在地震群逼近的危险性。

     

    Abstract: Objectives: Slow slip events (SSEs) are slow dislocation that occur in weak zones within the crust, and they may cause surface deformations and lead to slow earthquakes. However, the mechanism of SSEs and whether they will trigger earthquakes are still in the stage of discussion and speculation, and developing the new principles and methods. To further study the characteristics of SSEs and their relationship with earthquakes, we use GPS (Global positioning system) coordinate time series to invert SSEs. The spatiotemporal characteristics and evolution laws of SSEs are analyzed, and the relationship between slow slip events and earthquakes is discussed. Methods: The method is executed based on SLTM (Standard linear trajectory model) and NIF (Network inversion filter). Firstly, the slow slip coordinate time series are obtained by modeling GPS continuous coordinate time series using SLTM. The steps are repaired, and the gross errors, the constant, the steady state velocity, and the annual and semi-annual periodic season terms are removed. Then, NIF is used to construct the fault grid, and the elastic Green's function is introduced to describe the relationship between fault slip and surface displacement. Using the slow slip coordinate time series and NIF, the slip vectors on the fault grid and surface displacement vectors are inverted. Finally, the magnitude and frequency of the earthquakes before and after the slow slip event are calculated, and the possible relationship between slow slip events and earthquakes is analyzed. Results: Taking the 2018 slow slip event in Boso of Japan as an example, the results show that the active period of the slow slip ranges from the 156th to the 169th days; The maximum cumulative slip is about 11.3 cm, and the maximum slip rate is about 2.7 cm/day; The central area of the slow slip is located in the southeast of Boso Peninsula (34.8°N ~ 35.6°N, 140.2°E ~ 140.9°E), spreading southward slightly, and the depth of the slow slip changes from deep (about 23 km) to shallow (about 15 km); The frequency of regional earthquakes increases significantly during the slow slip event, and gradually recovers to normal in the following months. Therefore, the danger of approaching potential earthquake swarm can be identified from dynamic evolution of Boso slow slip. Conclusions: GPS plays an important role in the detection of SSEs, but it is difficult to detect short period SSEs within a few days due to the influence of various long period tectonic movement information, and the uneven distribution of GPS stations on land and sea leads to the decrease of spatial resolution. Hence, in the future work, we will further study the physical mechanism of SSEs in combination with other monitoring means such as strain gauge, tilt-meter and submarine pressure gauge.

     

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