Xu et al. (2025) A global intercomparison of SWOT and traditional nadir radar altimetry for monitoring river water surface elevation

Identification

• Journal: Remote Sensing of Environment
• Year: 2025
• Date: 2025-12-26
• Authors: Yue Xu, Frédéric Frappart, Guoqiang Tang, Guoqing Zhang, Peirong Lin, Liguang Jiang, Simon Michael Papalexiou, Fangfang Yao, Xiaoran Han, Jun Xia
• DOI: 10.1016/j.rse.2025.115219

Research Groups

• Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing, China
• ISPA, UMR 1391 INRAE/Bordeaux Sciences Agro, Villenave d’Ornon, France
• State Key Laboratory of Water Resources Engineering and Management, Wuhan University, China
• Key Laboratory of Biodiversity and Environment on the Qinghai-Tibetan Plateau, Xizang University, Lhasa, China
• State Key Laboratory of Tibetan Plateau Earth System Science, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
• School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
• Department of Civil Engineering, University of Calgary, Calgary, Canada
• School of Geosciences, University of South Florida, Tampa, FL, USA

Short Summary

This study presents the first global-scale intercomparison between SWOT’s wide-swath Ka-band InSAR and traditional nadir radar altimetry (Sentinel-3 and Sentinel-6) for monitoring river water surface elevation. The research identifies that while high-quality SWOT data aligns well with traditional altimetry (RMSE = 0.80 m), factors such as river width, ice cover, and extreme backscatter significantly modulate data consistency.

Objective

• To conduct a global validation of SWOT-derived river water surface elevation (WSE) by comparing it with established nadir radar altimetry (RA) databases and to identify the environmental and instrumental factors influencing their consistency.

Study Configuration

• Spatial Scale: Global (river networks monitored by SWOT and Sentinel-3/6 virtual stations).
• Temporal Scale: Not explicitly defined in the provided text, but covers the operational overlap of SWOT and Sentinel-3/6 missions (post-2022).

Methodology and Data

• Models used: Wide-swath SAR Interferometry (InSAR) at Ka-band (SWOT) and traditional along-track SAR-mode radar altimetry (Sentinel-3 and Sentinel-6).
• Data sources: SWOT river node products and Virtual Stations (VS) derived from Sentinel-3 and Sentinel-6 missions.
• Analysis Framework: Data were categorized into five quality levels ("good", "suspect", "degraded", "bad", and a combined "all" group). The study analyzed the impact of river width, river ice, backscattering coefficients ($\sigma^0$), and dark water fractions.

Main Results

• Accuracy by Quality Flag: "Good" quality data achieved a Root Mean Square Error (RMSE) of 0.80 m and a correlation coefficient (CC) of 0.85. "Suspect" data showed an RMSE of 1.62 m (CC = 0.78).
• Error in Low-Quality Data: RMSE rose sharply to 8.80 m for "degraded" data and 16.91 m for "bad" data.
• River Width Impact: Consistency with RA improved notably for rivers with widths exceeding 160 m.
• Environmental Factors: Frozen conditions reduced consistency, particularly in lower-quality categories (average CC reduction of 0.17 to 0.21).
• Backscatter Sensitivity: Both extremely low backscatter (dark water) and very high backscatter (specular ringing) were found to produce unrealistic WSE estimates.

Contributions

• Provides the first global-scale performance assessment of SWOT river WSE against traditional nadir altimetry.
• Establishes quantitative benchmarks for SWOT data quality across different node quality categories.
• Identifies critical thresholds (e.g., 160 m river width) and physical conditions (ice, backscatter extremes) that affect the reliability of SWOT measurements for hydrological research.

Funding

• Not specified in the provided text.

Citation

@article{Xu2025global,
  author = {Xu, Yue and Frappart, Frédéric and Tang, Guoqiang and Zhang, Guoqing and Lin, Peirong and Jiang, Liguang and Papalexiou, Simon Michael and Yao, Fangfang and Han, Xiaoran and Xia, Jun},
  title = {A global intercomparison of SWOT and traditional nadir radar altimetry for monitoring river water surface elevation},
  journal = {Remote Sensing of Environment},
  year = {2025},
  doi = {10.1016/j.rse.2025.115219},
  url = {https://doi.org/10.1016/j.rse.2025.115219}
}

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