Mon Feb 16, F. Flechtner
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Xiong, Yuhao, Liang, Jincheng, and Feng, Wei, 2025. Evaluating Terrestrial Water Storage, Fluxes, and Drivers in the Pearl River Basin from Downscaled GRACE/GFO and Hydrometeorological Data. Remote Sensing, 17(23):3816, doi:10.3390/rs17233816.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025RemS...17.3816X,
author = {{Xiong}, Yuhao and {Liang}, Jincheng and {Feng}, Wei},
title = "{Evaluating Terrestrial Water Storage, Fluxes, and Drivers in the Pearl River Basin from Downscaled GRACE/GFO and Hydrometeorological Data}",
journal = {Remote Sensing},
keywords = {GRACE/GFO, downscaled TWSA, XGBoost, SHAP, water balance, drought and flood, PRB},
year = 2025,
month = nov,
volume = {17},
number = {23},
eid = {3816},
pages = {3816},
abstract = "{What are the main findings? A joint inversion approach fuses GRACE/GFO
observations with WGHM outputs to produce a high-resolution TWSA
dataset for the Pearl River Basin (PRB). The downscaled product
outperforms WGHM, capturing seasonal and interannual variations
in water storage and fluxes. A joint inversion approach fuses
GRACE/GFO observations with WGHM outputs to produce a high-
resolution TWSA dataset for the Pearl River Basin (PRB). The
downscaled product outperforms WGHM, capturing seasonal and
interannual variations in water storage and fluxes. What is the
implication of the main finding? The downscaled TWSA enables
basin-scale monitoring in the PRB, capturing seasonal
accumulation, interannual shifts, and major extremes (e.g., the
2021 drought and wet-season floods) to improve risk assessment
and water management. Coupling the product with XGBoost─SHAP
could provide quantitative attribution of drivers
(precipitation, runoff, evapotranspiration, vegetation),
supporting process interpretation, forecasting, and decision-
making. The downscaled TWSA enables basin-scale monitoring in
the PRB, capturing seasonal accumulation, interannual shifts,
and major extremes (e.g., the 2021 drought and wet-season
floods) to improve risk assessment and water management.
Coupling the product with XGBoost─SHAP could provide
quantitative attribution of drivers (precipitation, runoff,
evapotranspiration, vegetation), supporting process
interpretation, forecasting, and decision-making. The Pearl
River Basin (PRB) is a humid subtropical system where frequent
floods and recurrent droughts challenge water management. GRACE
and GRACE Follow-On provide basin-scale constraints on
terrestrial water storage anomalies (TWSA), yet their coarse
native resolution limits applications at regional scales. We
employ a downscaled TWSA product derived via a joint inversion
that integrates GRACE/GFO observations with the high-resolution
spatial patterns of WaterGap Global Hydrological Model (WGHM).
Validation against GRACE/GFO shows that the downscaled product
outperforms WGHM at basin and pixel scales, with consistently
lower errors and higher skill, and with improved terrestrial
water flux (TWF) estimates that agree more closely with water
balance calculations in both magnitude and phase. The TWSA in
the PRB exhibits strong seasonality, with precipitation (P)
exceeding evapotranspiration (E) and runoff (R) from April to
July and storage peaking in July. From 2002 to 2022, the basin
alternates between multi-year declines and recoveries. On the
annual scale, TWSA covaries with precipitation and runoff, and
large-scale climate modes modulate these relationships, with El
Ni{\~n}o and a warm Pacific Decadal Oscillation (PDO) favoring
wetter conditions and La Ni{\~n}a and a cold PDO favoring drier
conditions. extreme gradient boosting (XGBoost) with shapley
additive explanations (SHAP) attribution identifies P as the
primary driver of storage variability, followed by R and E,
while vegetation and radiation variables play secondary roles.
Drought and flood diagnostics based on drought severity index
(DSI) and a standardized flood potential index (FPI) capture the
severe 2021 drought and major wet-season floods. The results
demonstrate that joint inversion downscaling enhances the
spatiotemporal fidelity of satellite-informed storage estimates
and provides actionable information for risk assessment and
water resources management.}",
doi = {10.3390/rs17233816},
adsurl = {https://ui.adsabs.harvard.edu/abs/2025RemS...17.3816X},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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