Mon Oct 13, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Jiang, Zhongshan, Zhang, Hui, Tang, Miao, Yang, Xinghai, Yuan, Linguo, Yuan, Yuan, Feng, Wei, and Zhong, Min, 2025. Tracking California's striking water storage gains attributed to intensive atmospheric rivers. Journal of Hydrology, 653:132804, doi:10.1016/j.jhydrol.2025.132804.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025JHyd..65332804J,
author = {{Jiang}, Zhongshan and {Zhang}, Hui and {Tang}, Miao and {Yang}, Xinghai and {Yuan}, Linguo and {Yuan}, Yuan and {Feng}, Wei and {Zhong}, Min},
title = "{Tracking California's striking water storage gains attributed to intensive atmospheric rivers}",
journal = {Journal of Hydrology},
keywords = {GNSS, Ground subsidence, Terrestrial water storage, Precipitation extremes, Atmospheric rivers},
year = 2025,
month = jun,
volume = {653},
eid = {132804},
pages = {132804},
abstract = "{California is highly vulnerable to extreme precipitation events due to
the dense landfall of atmospheric rivers (ARs) during the winter
months, often resulting in catastrophic consequences such as
widespread floods, mudslides, and landslides. This study focuses
on the recovery of daily variations in AR-driven terrestrial
water storage (TWS), which produces geodetically detectable
ground subsidence. We invert GNSS vertical positions to obtain
daily estimates of equivalent water height (EWH) through a
variational Bayesian principal component analysis (vbPCA) based
inversion scheme and track significant water gains during
record-setting winter months in four water years (WYs) 2011,
2017, 2019, and 2023. These precipitation extremes have resulted
in a substantial short-term increase in water storage, as
evidenced by the multi-source EWH datasets (GNSS, GRACE, and
NLDAS). Notably, WY 2023 experienced the highest snowfall due to
the landfalls of high-density, high-category ARs, while WY 2017
recorded the highest precipitation totals, driven by the most
frequent occurrence of hazardous ARs. Our findings further
highlight that GNSS can accurately detect exceptionally wet
hydrological events on short time scales, benefiting from an
improved signal-to-noise ratio due to substantial increase in
water storage. The results also indicate that while these
extreme water years can help alleviate surface subsidence in the
Central Valley caused by groundwater overexploitation, it is
insufficient to alter California's heavy reliance on groundwater
for its intensive agricultural activities. Our findings
demonstrate that GNSS is successful in tracking prodigious water
increases from short-term precipitation extremes that are weaker
than powerful hurricanes, illuminating the prospect of GNSS in
supporting water management and flood preparedness.}",
doi = {10.1016/j.jhydrol.2025.132804},
adsurl = {https://ui.adsabs.harvard.edu/abs/2025JHyd..65332804J},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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