Altimetry river water level retrieval over complex environments: assessment and diagnosis of different strategies
Satellite altimetry has been increasingly used in monitoring inland water bodies. Waveform retracking plays a major role in water level retrieval. However, there remain many challenges to retrieving accurate river water levels, especially for rivers surrounded by various water bodies. In this study, we investigated this problem by diagnosing six retrackers in the Yangtze River, where the environment is very complex. Results show that the official retracker (i.e., OCOG and threshold retrackers) used in Sentinel-3 product exhibits varying performance across 12 virtual stations, with RMSE in the range of 0.55-2.76 m. Surprisingly, no one retracker performs consistently well across all virtual stations. The enhanced multiple waveform persistent peak (MWaPP+) retracker was slightly better than the others. Taking multiple waveforms into consideration is a better strategy than single waveform-based ones. Poor performance is due to irregular waveforms, which are attributed to various water bodies surrounding the river. The number, elevation, and proportion of anomalous water bodies within the footprint are found decisive. In such complex environments, a combination of multiple strategies is needed to improve the accuracy of retrieved water levels. The proposed strategy, by combining FFSAR and MWaPP+, substantially enhanced accuracy and the number of observations. Nevertheless, we call for a round robin exercise to test more retracking strategies to deal with this problem. • Altimetry water level retrieval over complex environments is extensively assessed. • The fundamental theories of various retracking strategies are critically reviewed. • New strategies are proposed to improve nadir altimetry water level retrieval.
Authors
- Yanan Zhao (ORCID: https://orcid.org/0009-0006-7766-6005)
- Tian Xia (ORCID: https://orcid.org/0009-0006-6815-4008)
- Liguang Jiang
Institutions
- Southern University of Science and Technology (CN)
Publication Details
- Journal
- Science of Remote Sensing
- Published
- 2026-01-07
- DOI
- https://doi.org/10.1016/j.srs.2026.100363
- Primary Topic
- Flood Risk Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00