Characterizing the Seasonal Crustal Motion in Tianshan Area Using GPS, GRACE and Surface Loading Models

Wu, Yun; Zhao, Qian; Bao, Zhenan; Wu, Weiwei

doi:10.3390/rs9121303

Cited by 20 publications

(10 citation statements)

References 42 publications

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“…Moreira et al (2016) showed that the deviation between the monthly vertical component of GPS and GRACE was smaller than that of the global hydrological model among the 18 GPS stations of the Amazon basin, although the root mean squares (RMS) variation of the GPS series accounts for up to 70 %. Wu et al (2017) found that the seasonal crustal vertical deformation measured by GPS was more consistent with the results obtained by SLMs than GRACE, in the Tianshan area, and the correlation was better, mainly due to the influence of the atmospheric load. For the European region, some scholars have not combined GPS, GRACE and the hydrological model, and the load data sources used are different (e.g., Van Dam et al, 2007;Ma, 2017).…”

Section: Introductionsupporting

confidence: 74%

Comparisons of GRACE and GLDAS derived hydrological loading and the impacts on the GPS time series in Europe

Bian¹

2020

Acta Geodynamica Et Geomaterialia

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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. 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.

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Section: Introductionsupporting

confidence: 74%

Comparisons of GRACE and GLDAS derived hydrological loading and the impacts on the GPS time series in Europe

Bian¹

2020

Acta Geodynamica Et Geomaterialia

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“…Zou et al (2016) focused on the seasonal variation in the horizontal and vertical movements of southern Tibet by performing a joint analysis of GPS and GRACE data, and found that GPS-derived and GRACEderived seasonal oscillations are in good agreements. Wu et al (2017) investigated the seasonal crustal movements in Tianshan area using GPS, GRACE, and Surface Loading Models (SLMs), and confirmed that the consistency between the GPS and SLMs data was higher, which is probably due to the dominant atmospheric loading effects in this region. Li et al (2019) investigated the surface seasonal mass changes and vertical crustal deformation in North China using the measurements of GPS and GRACE.…”

Section: Grace Datamentioning

confidence: 83%

“…However, the data sets of GRACE and LSDM exhibit better consistency at most sites, as evidenced by the fact that the displacement time series of GRACE fits that of LSDM better. The main reason for the difference is that GRACE and LSDM represent smooth results limited by spatial resolution, while GPS observations are more sensitive to local effects (Wu et al, 2017). Figure 2 depicts the comparison of three data sets at sites SCXC and YNZD situated in Sichuan and Yunnan province, respectively.…”

Section: Comparison Of Deformations Derived From Three Techniquesmentioning

confidence: 99%

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

Xiang¹

2019

Acta Geodynamica Et Geomaterialia

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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 mid-and 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.

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“…The strongest recorded event was the M s 6.0 earthquake that struck in 1934 (Shen and Song 2008). Recent GPS measurements indicated that the compressional deformation of the Tianshan area is accommodated primarily by a series of W-E-trending fold-thrust belts with a slip rate of 1-2 mm/a and that Urumqi is moving toward the NE at a rate of 4-5 mm/a (Yang et al 2008;Wu et al 2017). The city is currently characterized by moderate to low seismic activity, and no major earthquake has occurred recently.…”

Section: Study Areamentioning

confidence: 99%

Seismic vulnerability assessment at urban scale using data mining and GIScience technology: application to Urumqi (China)

Liu

Wei

et al. 2019

Geomatics, Natural Hazards and Risk

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Seismic vulnerability assessments play a significant role in comprehensive risk mitigation efforts and seismic emergency planning, especially for urban areas with a high population density and a complex construction environment. Traditional approaches such as in situ fieldwork are accurate for conducting seismic vulnerability assessments of buildings; however, they are too much time and cost-consuming, especially in moderate to low seismic hazard regions. To address this issue, an integrated approach for a macroseismic vulnerability assessment composed of data mining methods and GIScience technology was presented and applied to Urumqi, China. First, vulnerability proxies were established via in situ data of buildings in the Tianshan District with an EMS-98 vulnerability classification scheme and two data mining methods, namely, support vector machine and association rule learning methods. Then, vulnerability proxies were applied to the Urumqi database, and the accuracy was validated. Finally, seismic risk maps were constructed through data consisting of direct damage to buildings and human casualties. The results indicated that the two data mining methods could achieve desirable accuracies and stabilities when estimating the seismic vulnerability. The seismic risk of Urumqi was estimated as Slight with a predicted number of 61,380 homeless people for a seismic intensity scenario of VIII.

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Characterizing the Seasonal Crustal Motion in Tianshan Area Using GPS, GRACE and Surface Loading Models

Cited by 20 publications

References 42 publications

Comparisons of GRACE and GLDAS derived hydrological loading and the impacts on the GPS time series in Europe

Comparisons of GRACE and GLDAS derived hydrological loading and the impacts on the GPS time series in Europe

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

Seismic vulnerability assessment at urban scale using data mining and GIScience technology: application to Urumqi (China)

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