Scale-Dependent Agreement of Hydrological Loading Displacements from GNSS, GRACE, and a Land Surface Model in the Heihe River Basin

Ground-based Global Navigation Satellite System (GNSS) vertical displacements provide an independent measure of hydrological loading, but their ability to resolve terrestrial water storage (TWS) variations in arid inland basins remains uncertain. This study compared vertical displacements from 15 GNSS stations within and around the Heihe River Basin with loading displacements derived from satellite-based GRACE and model-based Noah TWS anomalies. After removing non-hydrological signals from GNSS series, correlations among the network-mean vertical displacement for GNSS-GRACE, GNSS-Noah, and GRACE-Noah were 0.48, 0.49, and 0.74, respectively. Mean station-level correlations for the same comparisons were lower (0.38, 0.35, and 0.60, respectively), with weaker agreement within the basin interior. Time-series decomposition showed that GNSS captured inter-annual TWS variability more consistently than the seasonal cycle of TWS. GNSS generally peaks earlier than GRACE in the south but later in the north. Noah interannual variations diverged from both GNSS and GRACE, suggesting limitations in the model’s representation of arid-region hydrological processes. Overall, GNSS provides an independent constraint on long-term TWS variability and a diagnostic of land surface model performance. These findings support multisource monitoring of arid-basin water storage while highlighting the need for improved scale matching and in situ validation.

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Publication Details

Journal
Remote Sensing
Published
2026-10-26
DOI
https://doi.org/10.3390/rs18213673
Primary Topic
Geophysics and Gravity Measurements
Type
article
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article

Scale-Dependent Agreement of Hydrological Loading Displacements from GNSS, GRACE, and a Land Surface Model in the Heihe River Basin

Gaohong Yin, Jianmin Bian, Yue Gao, Jongmin Park et al.
Remote Sensing
Geophysics and Gravity Measurements
article

Scale-Dependent Agreement of Hydrological Loading Displacements from GNSS, GRACE, and a Land Surface Model in the Heihe River Basin

Gaohong Yin, Jianmin Bian, Yue Gao, Jongmin Park, Jingzun Mao, Rongchang Zhao, Yaohui Nan
article en

Abstract

Ground-based Global Navigation Satellite System (GNSS) vertical displacements provide an independent measure of hydrological loading, but their ability to resolve terrestrial water storage (TWS) variations in arid inland basins remains uncertain. This study compared vertical displacements from 15 GNSS stations within and around the Heihe River Basin with loading displacements derived from satellite-based GRACE and model-based Noah TWS anomalies. After removing non-hydrological signals from GNSS series, correlations among the network-mean vertical displacement for GNSS-GRACE, GNSS-Noah, and GRACE-Noah were 0.48, 0.49, and 0.74, respectively. Mean station-level correlations for the same comparisons were lower (0.38, 0.35, and 0.60, respectively), with weaker agreement within the basin interior. Time-series decomposition showed that GNSS captured inter-annual TWS variability more consistently than the seasonal cycle of TWS. GNSS generally peaks earlier than GRACE in the south but later in the north. Noah interannual variations diverged from both GNSS and GRACE, suggesting limitations in the model’s representation of arid-region hydrological processes. Overall, GNSS provides an independent constraint on long-term TWS variability and a diagnostic of land surface model performance. These findings support multisource monitoring of arid-basin water storage while highlighting the need for improved scale matching and in situ validation.

Remote SensingVol. 18(21)
Korea National University of Transportation (KR), Jilin University (CN), China Geological Survey (CN)
Openalex Percentile: Top 17%
Geophysics and Gravity Measurements
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Scale-Dependent Agreement of Hydrological Loading Displacements from GNSS, GRACE, and a Land Surface Model in the Heihe River Basin — Gaohong Yin, Jianmin Bian, et al. · Remote Sensing (2026) | TGRS Research Map | TGRS