顾及环境负载的青藏高原东南缘GNSS垂向坐标时序噪声模型研究

GNSS Vertical Coordinate Time Series Noise Model in Southeastern Tibet Plateau Based on Environmental Loading

  • 摘要: 准确辨识出全球导航卫星系统(Global Navigation Satellite System, GNSS)垂向坐标时间序列的最优噪声模型对于获取可靠的抬升或沉降变形速度场并评估速度不确定度至关重要。本文利用青藏高原东南缘在 2011年 1月 1日~2022年 12月 30日时间跨度的 94个GNSS连续站观测数据和环境负载模型数据,选用了 9种噪声模型对环境负载改正前后的GNSS垂向坐标时间序列进行噪声特性分析,并定量评价了环境负载效应的影响。研究结果表明,水文、大气、非潮汐海洋负载等环境负载对 GNSS垂向坐标时间序列均存在影响,环境负载改正后均方根减少百分比分别为-1.3%~22%, -1.4%~17.4%, -0.1%~1.3%,平均值分别为 8.7%, 6.7%, 0.6%,在以鲜水河-安宁河-则木河断裂带西侧的测站受水文负载影响更大,而东侧的测站受大气负载影响更大。经过环境负载改正后, 94个 GNSS连续站最优噪声模型主要表现为幂律噪声(Power-Law Noise, PL),其次是白噪声和 PL、闪烁噪声组合,环境负载改正前后最优噪声模型下估计的速度差值范围为-0.11~0.26 mm/a,速度不确定度差值范围为-0.33~0.16 mm/a。通过测站速度不确定度与高程,年均降雨量、经度,纬度的线性关系对 GNSS测站稳定性进行分析,青藏高原东南缘的年均降雨量、高程、经度、纬度对测站稳定性影响较小。

     

    Abstract: Objectives: Accurately identifying the optimal noise model for global navigation satellite system (GNSS) vertical time series is vital to obtain reliable uplift or subsidence deformation velocity fields and assess the associated uncertainties. Methods: In this study, we select 9 noise models (White Noise (WN)、 Flicker Noise (FN)、 Power-Law Noise (PL)、 Random Walk Noise(RW)、 WN+FN、 WN+PL、 WN+GGM、 WN+RW、 WN+RW+FN) to analyze the noise characteristics of GNSS vertical time series before and after environmental loading correction at 94 stations spanning from January 2011 to December 2022 in the southeastern Tibet Plateau. Results: Our results showed the root mean squares reduction was - 1.3%~22%, -1.4%~17.4%, and -0.1%~ 1.3%, with a mean value of 8.7%, 6.7%, 0.6% for all stations after removing the hydrological, atmospheric, and nontidal ocean loading deformation from the GNSS vertical coordinate time series, respectively, the hydrological loading has a greater impact in the west side of Xianshuihe-Anninghe-Zemuhe fault zone, the atmospheric load has a greater impact in east side of Xianshuihe-Anninghe-Zemuhe fault zone. The optimal noise model at all stations was mainly represented by PL, a combination of WN, PL, and FN before and after environmental loading correction. The value of velocity and its uncertainty before and after environmental loading correction based on optimal noise model varied from -0.11 to 0.26 mm/a and -0.33 to 0.16 mm/a. We analyzed the stability of GNSS stations through the linear relationship between GNSS vertical velocity uncertainty and elevation、 average annual rainfall 、 longitude、 latitude, the results of correlations coefficient was 0.08, 0.07, 0.11, and 0.25, respectively, implying the average annual rainfall, elevation, longitude, and latitude have little impact on station stability in the southeastern Tibet Plateau. Conclusions: Our research suggest that the optimal noise models at most stations in the southeastern Tibet Plateau was PL. This results provides a reference for subsequent reasonable acquisition of GNSS velocity and its uncertainy in the southeastern Tibet Plateau.

     

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