Mon Aug 24, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Park, Heejun, Hwang, Seokhwan, Yoon, Jung Soo, Kang, Narae, and Lee, Sujong, 2026. High–Resolution Daily Groundwater Storage Estimation over the Korean Peninsula via GRACE–GLDAS Integration. Remote Sensing, 18(11):1811, doi:10.3390/rs18111811.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2026RemS...18.1811P,
author = {{Park}, Heejun and {Hwang}, Seokhwan and {Yoon}, Jung Soo and {Kang}, Narae and {Lee}, Sujong},
title = "{High-Resolution Daily Groundwater Storage Estimation over the Korean Peninsula via GRACE--GLDAS Integration}",
journal = {Remote Sensing},
keywords = {GRACE/GRACE-FO, GLDAS-CLSM, groundwater storage, temporal disaggregation, drought propagation, anthropogenic abstraction, Korean Peninsula},
year = 2026,
month = jun,
volume = {18},
number = {11},
eid = {1811},
pages = {1811},
abstract = "{By integrating GRACE and GLDAS, we reconstruct a high-resolution daily
groundwater storage anomaly (GWSA) time series for the Korean
Peninsula from 2002 to 2025. The framework demonstrates strong
agreement with in situ groundwater observations and effectively
captures sub-monthly variability, including extreme drought-
driven depletion events. What are the main findings? The
GRACE--GLDAS fusion reconstructs daily GWSA (2002--2025) with
strong agreement with in situ groundwater levels (up to 0.72
after deseasonalization). During the 2013--2015 drought, the
framework accurately reproduces groundwater depletion dynamics
driven by both climate and anthropogenic activity. The
GRACE--GLDAS fusion reconstructs daily GWSA (2002--2025) with
strong agreement with in situ groundwater levels (up to 0.72
after deseasonalization). During the 2013--2015 drought, the
framework accurately reproduces groundwater depletion dynamics
driven by both climate and anthropogenic activity. What is the
implication of the main finding? The 22-year daily GWSA record
overcomes GRACE's traditional limitation, enabling high-
frequency groundwater monitoring. This framework can be applied
to other data-sparse regions to enhance regional-scale
hydrological monitoring. The 22-year daily GWSA record overcomes
GRACE's traditional limitation, enabling high-frequency
groundwater monitoring. This framework can be applied to other
data-sparse regions to enhance regional-scale hydrological
monitoring. Quantifying changes in groundwater storage (GWS)
remains a fundamental challenge in hydrology, given the sparsity
of long-term in situ monitoring networks and the inherent
difficulty of direct subsurface observation. Although GRACE and
GRACE-FO satellite missions provide a means of tracking total
terrestrial water storage at the continental scale, their coarse
spatial resolution (\raisebox{-0.5ex}\textasciitilde300 km) and
monthly temporal sampling limit their direct applicability to
regional groundwater studies. Here, we present a spatio-temporal
disaggregation and data fusion framework for reconstructing
daily GWS anomalies (GWSAs) across the Korean Peninsula,
integrating GRACE/GRACE-FO Mascon solutions with the GLDAS
Catchment Land Surface Model (CLSM). The approach leverages
satellite-derived mass variations to constrain the model's long-
term anomaly structure while retaining the high-frequency
temporal dynamics of land-surface modeling. The framework is
evaluated against in situ bedrock monitoring well records from
five sites: Seoul, Cheongyang, Uiseong, Imsil, and Wonju. Raw
time-series correlations range from R = 0.14 to 0.70; upon
removal of the monthly climatology to isolate non-seasonal
variability, R improves to 0.49--0.72 across all sites, reaching
0.718 in Seoul and 0.707 in Cheongyang, with Cheongyang's RMSE
declining from 8.847 to 7.574 cm. These results indicate that
the GRACE-CLSM fusion framework captures genuine sub-monthly
groundwater dynamics beyond the dominant seasonal cycle. To our
knowledge, this represents the first reconstruction of daily GWS
changes for the Korean Peninsula with explicit preservation of
spatial mass conservation, and the resulting dataset has direct
utility for operational groundwater monitoring in a region
subject to hydroclimatic variability.}",
doi = {10.3390/rs18111811},
adsurl = {https://ui.adsabs.harvard.edu/abs/2026RemS...18.1811P},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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