Mon Aug 24, F. Flechtner
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Ma, Chongya, Liu, Jiping, and Fu, Guobin, 2026. Spatial and Temporal Variability of Terrestrial Water Storage and Their Relationship with Groundwater Level with GRACE, GLDAS and Observations: A Case Study of Murray–Darling Basin. Remote Sensing, 18(13):2206, doi:10.3390/rs18132206.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2026RemS...18.2206M,
author = {{Ma}, Chongya and {Liu}, Jiping and {Fu}, Guobin},
title = "{Spatial and Temporal Variability of Terrestrial Water Storage and Their Relationship with Groundwater Level with GRACE, GLDAS and Observations: A Case Study of Murray--Darling Basin}",
journal = {Remote Sensing},
keywords = {GLDAS, GRACE, groundwater level, hierarchical cluster analysis (HCA), Murray--Darling Basin (MDB), terrestrial water storage (TWS)},
year = 2026,
month = jul,
volume = {18},
number = {13},
eid = {2206},
pages = {2206},
abstract = "{What are the main findings? A clear temporal variability of terrestrial
water storage (TWS) with positive and negative anomalies, as
well as declining and increasing trends. Strong correlation
between TWS and rainfall, evaporation and runoff, and some
similarities and differences between TWS-derived groundwater
storage changes and in situ groundwater-level observation
changes. A clear temporal variability of terrestrial water
storage (TWS) with positive and negative anomalies, as well as
declining and increasing trends. Strong correlation between TWS
and rainfall, evaporation and runoff, and some similarities and
differences between TWS-derived groundwater storage changes and
in situ groundwater-level observation changes. What are the
implications of the main findings? The temporal variability
highlights the caveats and limitations of existing TWS trend
analysis based on relatively short time periods. The
correlations can support sustainable groundwater management by
assessing the impacts of future climate change and variability
and by identifying regions where groundwater extraction is
larger than natural recharge to serve water allocation planning.
The temporal variability highlights the caveats and limitations
of existing TWS trend analysis based on relatively short time
periods. The correlations can support sustainable groundwater
management by assessing the impacts of future climate change and
variability and by identifying regions where groundwater
extraction is larger than natural recharge to serve water
allocation planning. Spatial and temporal patterns of
terrestrial water storage (TWS), and their relationship with
groundwater levels, were investigated with the Gravity Recovery
and Climate Experiment (GRACE) satellite data, the Global Land
Data Assimilation System (GLDAS) land surface model results, and
climate observations for the Murray--Darling Basin (MDB). The
results show that: (1) TWS displays a clear temporal
variability: a negative TWS anomaly with a declining trend
during 2002--2009, a positive TWS anomaly with a decreasing trend
during 2010--2017, and a period of mixed positive and negative
TWS anomalies being accompanied by an increasing trend from 2018
to 2025; (2) five dominant cluster patterns were identified that
explain the spatial variability of temporal TWS across the MDB;
(3) overall, TWS temporal variability is strongly correlated
with rainfall, although it is weak at certain locations; (4) TWS
is also influenced by evaporation (both actual and potential
evapotranspiration, AET and PET) and runoff, and a combined
model significantly improves the overall performance in
explaining TWS temporal variability; and (5) TWS-derived
groundwater storage changes show both similarities and
differences in comparison with groundwater level observation
changes, reflecting complex hydrogeological processes and the
influence of human activities such as groundwater extraction.
These findings provide valuable insights to support improved
groundwater resource management with GRACE satellite information
and land surface models.}",
doi = {10.3390/rs18132206},
adsurl = {https://ui.adsabs.harvard.edu/abs/2026RemS...18.2206M},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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