Sadki et al. (2026) Improving large-scale river routing models with ESA long-term CCI discharge data assimilation: advancing accuracy for climate studies

Identification

• Journal: Hydrology and earth system sciences
• Year: 2026
• Date: 2026-10-02
• Authors: Malak Sadki, Gaëtan Noual, Simon Munier, Vanessa Pedinotti, Kaushlendra Verma, Clément Albergel, Sylvain Biancamaria, Alice Andral
• DOI: 10.5194/hess-30-6159-2026

Research Groups

• Magellium (France)
• CLS (France)
• CNRM (France)
• European Space Agency Climate Office (United Kingdom)
• Laboratoire d’Etudes en Géophysique et Océanographie Spatiales (LEGOS), Université de Toulouse, CNES/CNRS/IRD/UT3 (France)

Short Summary

This study evaluates the effectiveness of long-term satellite-derived ESA Climate Change Initiative (CCI) water surface elevation (WSE) and discharge products in improving large-scale hydrological simulations through data assimilation. The results demonstrate that assimilating these products can improve model performance, but the magnitude and reliability of the improvements depend on the interaction between product type and quality, temporal and spatial sampling, model configuration, and basin-specific hydrological processes.

Objective

• Investigate the added-value of long-term satellite-based data assimilation for improving large-scale hydrological modeling in African river basins.
• Evaluate the potential of CCI discharge assimilation within two conceptual different models: ISBA-CTRIP global river routing model and MGB regional hydrological model.

Study Configuration

• Spatial Scale: Continental to basin scale
• Temporal Scale: 20 years (2000–2020)

Methodology and Data

• Models used: ISBA-CTRIP, MGB
• Data sources: ESA Climate Change Initiative (CCI) WSE and discharge products

Main Results

• Assimilating CCI-derived WSE and discharge products can improve model performance in both the Niger and Congo basins.
• The magnitude of improvement depends on the product type and quality, temporal and spatial sampling, model configuration, and basin-specific hydrological processes.
• Discharge assimilation generally outperformed WSE anomaly assimilation due to direct representation of discharge in routing models.

Contributions

• This study contributes to filling the gap in evaluating the effectiveness of long-term satellite-derived data assimilation for improving large-scale hydrological modeling in African river basins.
• The results demonstrate the potential of CCI discharge assimilation in improving model performance, but highlight the need for careful consideration of product type and quality, temporal and spatial sampling, model configuration, and basin-specific hydrological processes.

Funding

• This research was funded by the European Space Agency (ESA) Climate Change Initiative (CCI) project.

Citation

@article{Sadki2026Improving,
  author = {Sadki, Malak and Noual, Gaëtan and Munier, Simon and Pedinotti, Vanessa and Verma, Kaushlendra and Albergel, Clément and Biancamaria, Sylvain and Andral, Alice},
  title = {Improving large-scale river routing models with ESA long-term CCI discharge data assimilation: advancing accuracy for climate studies},
  journal = {Hydrology and earth system sciences},
  year = {2026},
  doi = {10.5194/hess-30-6159-2026},
  url = {https://doi.org/10.5194/hess-30-6159-2026}
}