Mon Oct 13, F. Flechtner
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Chen, Tao, Pan, Yuanjin, Jiao, Jiashuang, and He, Meilin, 2025. Integrating GNSS and GRACE Observations to Investigate Water Storage Variations Across Different Climatic Regions of China. IEEE Transactions on Geoscience and Remote Sensing, 63:TGRS.2025, doi:10.1109/TGRS.2025.3563095.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025ITGRS..63S3095C,
author = {{Chen}, Tao and {Pan}, Yuanjin and {Jiao}, Jiashuang and {He}, Meilin},
title = "{Integrating GNSS and GRACE Observations to Investigate Water Storage Variations Across Different Climatic Regions of China}",
journal = {IEEE Transactions on Geoscience and Remote Sensing},
keywords = {Climatic variability in China, global navigation satellite system (GNSS) and Gravity Recovery and Climate Experiment (GRACE) observations, hydrological dynamics, joint inversion, terrestrial water storage (TWS)},
year = 2025,
month = jan,
volume = {63},
eid = {TGRS.2025},
pages = {TGRS.2025},
abstract = "{China has a vast territory, complex hydrogeological structures, and a
diverse and variable climate. However, the sparse distribution
of global navigation satellite system (GNSS) stations presents a
challenge to ensuring the accuracy of hydrological inversions
across such a large area using GNSS observations alone. To
address this, we integrate GNSS and Gravity Recovery and Climate
Experiment (GRACE) observations to jointly invert changes in
terrestrial water storage (TWS) across different climate zones
in China. Using a checkerboard load mass source, we first test
the feasibility of the joint inversion method. The results show
that compared to the GNSS-only inversion, the root-mean-square
error (RMSE) of the joint inversion is reduced by 23.25\%
(\raisebox{-0.5ex}\textasciitilde18.64 mm). This demonstrates
that the joint inversion method captures more detailed
spatiotemporal variations of TWS, confirming its feasibility and
advantages. Moreover, the synthetic test results of the
chessboard load mass sources with different station
distributions reveal that as the average station spacing within
the study area decreases, the TWS variations obtained from the
joint inversion method become more reliable. We then apply this
method to actual GNSS vertical displacements, initially focusing
on the seasonal variations in TWS across six climatic zones in
China. The results indicate that the joint inversion method more
effectively captures regional TWS variations, particularly in
areas with limited precipitation (e.g., northwest China).
However, due to the limitations in station coverage, the
improvements are somewhat constrained, although significant
potential remains. In contrast, in regions with abundant
precipitation (e.g., southwest China), TWS variations obtained
through different data exhibit greater consistency. Finally, we
analyze the relationship between TWS variations and
hydrometeorological data (i.e., precipitation and temperature)
across the six climate zones. The results show that there is a
significant correlation between TWS variations and
hydrometeorological data, and the former shows a time lag of
1{\textendash}2 months relative to the latter, a phenomenon that
may be attributed to the complex transmission mechanism of TWS.
This research highlights the potential of space geodetic
techniques (e.g., GNSS and GRACE) in hydrological climatology
and hydrogeodesy, providing valuable insights into the
interactions between TWS variations and climate dynamics.}",
doi = {10.1109/TGRS.2025.3563095},
adsurl = {https://ui.adsabs.harvard.edu/abs/2025ITGRS..63S3095C},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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