Monitoring water surface elevation and river width using SWOT: insights into observation geometry, phase noise, and geomorphic modulation in the Yangtze River

For inland rivers with complex topographies, however, conventional nadir altimeters often fail to meet accuracy requirements and exhibit substantial spatial sampling limitations. Fortunately, the Surface Water and Ocean Topography (SWOT) Satellite, with its wide swath, high spatial resolution, and improved vertical precision, offers new opportunities for the dynamic monitoring of rivers and small water bodies. However, the short duration since SWOT data became available means that existing validations of SWOT over rivers are often limited by insufficient samples, coarse temporal alignment with in-situ data, and a lack of physical explanation for accuracy variations across diverse basins. Here, we used in-situ water levels from 52 monitoring stations located within the Yangtze River Basin and river width data extracted from Sentinel-2 imagery to evaluate the accuracy of the SWOT Water Surface Elevation (WSE) and river width (RW). The results showed that although the SWOT WSE achieved moderate accuracy across all 52 monitoring stations (MAE = 0.42 m), the 28 waterway survey stations located along the Yangtze River main stem exhibited higher accuracy (MAE = 0.36 m) than the 15 monitoring stations on natural tributaries (MAE = 0.50 m) among the 43 natural river-channel monitoring stations. In addition, the nine reservoir stations were reported separately because they were governed by fundamentally different physical error mechanisms. Regrettably, the SWOT RW showed relatively low accuracy with a mean normalized MAE/m of 0.32 (where MAE/m means MAE/RW), with a spatial pattern similar to WSE, with higher accuracy along the gently sloping and wide-channel sections of the Yangtze River main stem where channel gradients are gentler and river widths are larger (MAE/m = 0.21), but its accuracy decreased in the Jinsha River and other tributaries (MAE/m = 0.50). On this basis, we investigated the physical processes through which geomorphological conditions regulated the accuracy of SWOT WSE, focusing on two key aspects: observation geometry (e.g. incidence angle, the angle between the river channel and the SWOT track, and interferometric baseline stability) and phase noise (e.g. RW, sandbars, river channel meandering, steep riverbanks, and river channel slope). The analysis demonstrated that the accuracy of SWOT in complex basins is determined by the degree of alignment between the dynamic observation geometry and static geomorphic characteristics. In summary, the SWOT provides a high-accuracy WSE but a moderate RW dataset and enables the dynamic monitoring of inland rivers and small water bodies globally in near-real-time.