Acta Geodynamica et Geomaterialia | 2019

Seasonal crustal deformations around the eastern Tibetan Plateau constrained by GPS, GRACE and hydrological model

 

Abstract


In order to characterize the seasonal crustal deformations induced by hydrological loading around the eastern Tibetan Plateau, the data sets of Global Positioning System (GPS), Land Surface Discharge Model (LSDM), and Gravity Recovery and Climate Experiment (GRACE) at 24 sites situated in this region are collected. The hydrological loading effects around the eastern Tibetan Plateau exhibit strong latitude dependence. The Root Mean Square (RMS) values tend to occurrence a downward trend as the latitude increases, and large RMS values are cumulated at the sites located in the low-latitude area of this region. Meanwhile, the amplitude of the annual signals of three data sets modeled by Monte Carlo Singular Spectrum Analysis (MCSSA) in lowlatitude area is larger than midand high-latitude area. Then, Cross Wavelet Transform (XWT) is adopted to assess the consistency between different data sets. The XWT-based semblance of GPS/GRACE above 0.9 are observed at 67 % of the sites, while it reaches 79 % for GPS/LSDM, implying LSDM can well model the hydrological loading deformations around the eastern Tibetan Plateau in comparison with GRACE. We also evaluate the effects of hydrological loading on GPS observations from the variations of RMS values, noise properties, and velocity uncertainties. After applying hydrological loading correction, the reduction of RMS values and velocity uncertainties appears at most sites. Moreover, the magnitude of Flicker Noise (FN) in most GPS observations is decreased, whereas the magnitude of White Noise (WN) is increased accordingly. The results suggest that applying hydrological loading correction can reduce the magnitude of FN in most GPS observations, and improve the precision of velocity estimation. ARTICLE INFO

Volume None
Pages 429-440
DOI 10.13168/agg.2019.0036
Language English
Journal Acta Geodynamica et Geomaterialia

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