The surface displacement caused by hydrological loading makes an important contribution to the non-linear crustal movement observed at the International Global Navigation Satellite System Service (IGS) stations. In this paper, the amplitude, correlation, and root mean square (RMS) of the vertical displacement time series signals of 47 IGS stations are used to analyze which data of Gravity Recovery and Climate Experiment (GRACE) or Global Land Data Assimilation System (GLDAS) can better reflect the hydrological load effect in Europe. The results show that in Europe, the hydrological load effect calculated based on GRACE data is more accurate than that of GLDAS, which has not been reported before. Then, the relationship between the GPS height and GRACE load deformation in terms of annually-oscillating signals, correlation, and phase is analyzed by using singular spectrum analysis, the Pearson correlation coefficient, and wavelet coherence (WTC). It was found that GPS and GRACE agree at some stations (e.g., BOR1 and ZIMM), while they differ significantly in amplitude and phase at other stations (e.g., KIRU and NOT1), indicating that not all GRACE-derived displacements of IGS stations can clearly explain their nonlinear motion. and The correlation coefficients between GPS and GRACE are higher than 0.7 at 85 % of stations. Amongst them, the values are obviously greater than 0.8 (e.g., ZIMM and LAMA) around inland areas and high mountains, and even less than 0.6 (e.g., ANKR and KIRU) along the coast of the Mediterranean ocean, which more precisely shows that the hydrological load effect has obvious spatial and regional characteristics compared with previous studies. In addition, the relative phase of the WTC solution is basically consistent under non-detrend and detrend, which shows that the relative phase difference of each station is only related to the nonlinear movement and not to the linear trend caused by the tectonic deformation. Finally, we study the influence of GRACE hydrological load on the RMS of GPS height, which is reduced by 24.60 % on average, and the reduction rate distribution of the RMS is in good agreement with the spatial distribution of the correlation coefficient.
In this paper, a scheme of signal extraction and modeling for GNSS position time series based on Monte Carlo Multi-channel Singular Spectrum Analysis (MC-MSSA) is introduced, which can effectively consider the spatial correlation of different directions by processing the different components of position time series at the same time. Meanwhile, the Monte Carlo significance test is utilized to distinguish the signal from the colored noise. By comparing with Singular Spectrum Analysis (SSA), it can be confirmed that MSSA has better signal extraction and modeling performance by taking into account the correlation of different channels. Then, taking the LHAZ station as an example, MC-MSSA is utilized to simultaneously model the three components of GNSS position time series, and the trend and periodic signals are respectively identified by Kendall nonparametric test and W-correlation correlation analysis. The result denotes that MC-MSSA can effectively model the tectonic and non-tectonic signals of GNSS position time series, and the modeled signals can more intuitively reflect the dynamic movement of the station. Finally, based on the MC-MSSA-modeled tectonic signal, we characterize the crustal deformations around the eastern Tibetan Plateau, mainly including the crustal movement and strain rate change. The results suggest that the pushing movement of the Tibetan Plateau from the Indian plate is blocked by the South China block, and the crustal movement rate is obviously decreased and appears a right-handed movement trend. Meanwhile, the junction of the Tibetan Plateau and South China block has accumulated a certain amount of stress, and the tectonic activity at the junction is relatively strong and still belongs to the dangerous zone of seismic activity.