Fri Apr 10, F. Flechtner
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Ghaneei, Parnian and Moradkhani, Hamid, 2026. An Effective Monitoring of Evolving Groundwater Drought via Multivariate Data Assimilation and Machine Learning. Water Resources Research, 62(2):e2025WR041565, doi:10.1029/2025WR041565.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2026WRR....6241565G,
author = {{Ghaneei}, Parnian and {Moradkhani}, Hamid},
title = "{An Effective Monitoring of Evolving Groundwater Drought via Multivariate Data Assimilation and Machine Learning}",
journal = {Water Resources Research},
keywords = {groundwater drought, land surface modeling, data assimilation, machine learning},
year = 2026,
month = feb,
volume = {62},
number = {2},
eid = {e2025WR041565},
pages = {e2025WR041565},
abstract = "{Groundwater drought represents one of the most pervasive and difficult-
to-monitor forms of water scarcity, threatening the reliability
of freshwater supply for over 2 billion people worldwide,
agricultural productivity, and ecosystem health. Despite its
critical importance, monitoring groundwater drought with high
spatial and temporal resolution remains challenging due to
limited in situ observations, coarse-resolution satellite data,
and uncertainties in models. In this study, we introduce an
observation-informed approach for producing daily groundwater
drought maps at 1/8{\textdegree} resolution across the
contiguous United States (CONUS). Leveraging high-performance
computing, we jointly assimilate Soil Moisture Active Passive
soil moisture and GRACE-FO terrestrial water storage data into
the Noah-MP land surface model to enhance the representation of
groundwater─surface water interactions while accounting for
uncertainties, enabling a more accurate representation of
groundwater drought dynamics. Considering the spatial and
temporal complexities of drought patterns, we employ the Growing
Neural Gas, a machine learning-based pattern recognition
algorithm, to identify emergent, evolving, and region-specific
behaviors of groundwater drought. The results reveal the onset
of distinct and persistent dry clusters in recent years across
the contiguous United States (CONUS), identifying the severe
groundwater drought conditions that notably impacted large
regions of both the Western and Northeastern CONUS. Our findings
highlight the need to reassess groundwater resilience
strategies, especially as droughts intensify and persist over
large domains.}",
doi = {10.1029/2025WR041565},
adsurl = {https://ui.adsabs.harvard.edu/abs/2026WRR....6241565G},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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