He et al. (2025) Seasonal and Interannual Variations in Hydrological Dynamics of the Amazon Basin: Insights from Geodetic Observations

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Identification

• Journal: Remote Sensing
• Year: 2025
• Date: 2025-08-07
• Authors: Meilin He, Tao Chen, Yuanjin Pan, Lv Zhou, Yifei Lv, Lewen Zhao
• DOI: 10.3390/rs17152739

Research Groups

Not specified

Short Summary

This study analyzes spatiotemporal terrestrial water storage (TWS) changes in the Amazon Basin from 2002 to 2021 using GRACE and GNSS data, concluding that ENSO-driven precipitation anomalies are the primary drivers of interannual hydrological variability.

Objective

• To investigate the spatiotemporal dynamics of hydrological mass changes in the Amazon Basin and evaluate the relationship between GRACE-derived TWS and GNSS-measured vertical displacement.

Study Configuration

• Spatial Scale: Amazon Basin
• Temporal Scale: 2002–2021

Methodology and Data

• Models used: Principal Component Analysis (PCA), existing hydrological models (for comparison).
• Data sources: GRACE and GRACE-FO satellite missions, Global Navigation Satellite System (GNSS) vertical displacement measurements.

Main Results

• Spatial Heterogeneity: Annual TWS amplitude exceeds 0.65 m near the Amazon River and drops below 0.25 m in peripheral mountainous regions.
• Data Correlation: A strong correlation (mean Pearson coefficient = 0.72) exists between GNSS vertical displacement and GRACE-derived hydrological load deformation; incorporating GNSS data reduces the root mean square (RMS) error by 35%.
• Model Limitation: Hydrological models that neglect groundwater dynamics are found to underestimate hydrological load deformation.
• Climate Coupling: PCA of GNSS data reveals that abrupt interannual TWS fluctuations (notably between 2010 and 2021) align with extreme precipitation events modulated by the El Niño–Southern Oscillation (ENSO).

Contributions

• Establishes a methodological framework for integrating satellite gravity data with GNSS measurements to refine hydrological load deformation estimates.
• Clarifies the role of ENSO in modulating basin-scale hydrological variability in the Amazon, providing a basis for predicting extreme hydrological events under climate warming.

Funding

Not specified

Citation

@article{He2025Seasonal,
  author = {He, Meilin and Chen, Tao and Pan, Yuanjin and Zhou, Lv and Lv, Yifei and Zhao, Lewen},
  title = {Seasonal and Interannual Variations in Hydrological Dynamics of the Amazon Basin: Insights from Geodetic Observations},
  journal = {Remote Sensing},
  year = {2025},
  doi = {10.3390/rs17152739},
  url = {https://doi.org/10.3390/rs17152739}
}