Summary Field surveys for monitoring river morphology are resource‐intensive, especially in large river systems. Earth observation (EO) satellites provide valuable alternatives, yet the integrated use of multiple missions remains underexplored. This study develops a framework that combines Landsat, Sentinel‐1, Sentinel‐2 and Ice, Cloud and Land Elevation Satellite‐2 (ICESat‐2) data to estimate periodically inundated bed topography and morphological change in the large alluvial Jamuna River. The method achieved an accuracy of m of RMSE in topography estimation, with a tendency to overestimate elevations with a mean bias of 1.24 m while preserving slope. By relating water occurrence probability to elevation, morphological changes were quantified for elevation bands, enabling the estimation of area and volume dynamics while accounting for interannual hydrological variability. Compared with the earlier EO‐based morphological monitoring tool—which tends to overestimate erosion and accretion areas—the proposed framework reduced false detections (%) by accounting for hydrological variability and refining change‐classification thresholds. Estimated volumes were comparable in magnitude to EO‐based estimates reported in the literature. However, validation with field data revealed that erosion and accretion volumes were underestimated primarily due to the inability to detect changes in aperiodic bed and an inconsistent temporal scale of field and satellite data. Despite these limitations, the method successfully captured dominant reach‐scale morphological processes and is suitable for deriving first‐order estimates of morphological changes in large rivers with seasonally fluctuating water levels. While further research is needed to better quantify errors/uncertainties and validate the SWOT‐based water surface elevation profile correction, this work lays a foundation for using multi‐satellite EO data for large‐scale river morphological assessments.
Bhattarai et al. (Thu,) studied this question.