Thu Dec 12, F.Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Li, Huixiang, Pan, Yun, Yeh, Pat J. -F., Zhang, Chong, Huang, Zhiyong, Xu, Li, Wang, Haigang, Zeng, Linghai, Gong, Huili, and Famiglietti, James S., 2024. A New GRACE Downscaling Approach for Deriving High-Resolution Groundwater Storage Changes Using Ground-Based Scaling Factors. Water Resources Research, 60(11):2023WR035210, doi:10.1029/2023WR035210.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2024WRR....6035210L,
author = {{Li}, Huixiang and {Pan}, Yun and {Yeh}, Pat J. -F. and {Zhang}, Chong and {Huang}, Zhiyong and {Xu}, Li and {Wang}, Haigang and {Zeng}, Linghai and {Gong}, Huili and {Famiglietti}, James S.},
title = "{A New GRACE Downscaling Approach for Deriving High-Resolution Groundwater Storage Changes Using Ground-Based Scaling Factors}",
journal = {Water Resources Research},
keywords = {GRACE, groundwater storage change, groundwater level change, scaling factor, Scaling factor, North China plain},
year = 2024,
month = nov,
volume = {60},
number = {11},
pages = {2023WR035210},
abstract = "{To compensate for the coarse resolution of groundwater storage (GWS)
estimation by the Gravity Recovery and Climate Experiment
(GRACE) satellites and make better use of available observed
groundwater-level (GWL) data in some aquifers, a ground-based
scaling factor (SF) method is proposed here to derive high-
resolution GRACE GWS estimates. Improvement is achieved by using
the gridded SF derived from assimilating ground-based GWL
observations. The proposed SF method is tested on the North
China Plain (NCP, {\ensuremath{\sim}}140,000 km$^{2}$), where a
dense network of observation wells and a consistently estimated
specific yield (SY) data set are available, to demonstrate its
effectiveness and practical applications. The sensitivities of
SF-estimated GWS accuracy to the specification of SY and the
assimilation of GWL observation data are explored through four
designed numerical experiments. Results show that this novel
ground-based method can reduce the impact of SY uncertainty on
GWS estimates, particularly in regions with more pronounced
regional GWS trends. The accuracy of SF-estimated GWS is
primarily determined by whether the assimilated wells can
reflect the regionally averaged GWS trend. GWS accuracy is less
dependent on the number of available wells assimilated. The
estimated GWS trend (2004{\textendash}2015) in NCP is ‑32.6
{\ensuremath{\pm}} 1.3 mm/yr (‑4.6 {\ensuremath{\pm}} 0.2
km$^{3}$/yr), with contrasting GWS trends found in the west
Piedmont Plain ({\ensuremath{\sim}}54,000 km$^{2}$, with a loss
of ‑66.8 mm/yr) and the coastal Eastern Plain
({\ensuremath{\sim}}20,000 km$^{2}$, and a gain of +7.2 mm/yr).
Despite the limitations of regional and time scale dependence
inherent in SF method, this study highlights the benefits of
assimilating in situ observed GWL data instead of using model
simulations in estimating SF to downscale GRACE GWS to the
higher-resolution that is desired by local water resources
management.}",
doi = {10.1029/2023WR035210},
adsurl = {https://ui.adsabs.harvard.edu/abs/2024WRR....6035210L},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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