Role of Land–Water Classification and Manning's Roughness Parameter in Space-Borne Estimation of Discharge for Braided Rivers: A Case Study of the Brahmaputra River in Bangladesh

摘要

The proposed Surface Water and Ocean Topography (SWOT) mission will provide global, space-based estimates of water elevation, its temporal change, and its spatial slope for terrestrial water bodies. Using derivations of water slope from the Shuttle Radar Topography Mission (SRTM) elevation data, river bathymetry and Manning''s equation, the potential of SWOT for discharge estimation of large braided rivers in humid climates, such as the Brahmaputra river, was found to be promising (Jung , in Earth Surface Processes and Landforms, 2010). In this study we extend the work on assessing SWOT for braided rivers to understand the sensitivity of two river hydraulic parameters to discharge estimation: 1) section factor $({rm AR}^{2/3})$ derived from land–water classification and in situ river bathymetry and 2) Manning''s roughness coefficient. For braided rivers, the first parameter, is intimately dependent on how braided rivers are classified of the multiple channels (water) and in-stream braided bars (land) that consequently dictates the accuracy of wetted perimeter and area of flow estimation from water elevation data. We show that the use of the minimum water elevation data at a river cross section minimizes estimation of section factor which consequently minimizes outlier discharge estimation reported in the Jung study. We also show that by treating roughness coefficient “flexible” as a calibration parameter, discharge estimation from SRTM elevation data can be further improved through trial and error manual optimization. Our sensitivity study illustrates the value of treating section factor and roughness coefficient as calibration parameters for data assimilation systems that use SWOT observables to estimate river discharge in braided rivers.