Integrating satellite altimetry with hydrologic modeling derives daily continuous river discharge for ungauged basins: Implications for the SWOT mission

Abstract:

The combination of altimetry-derived water levels and hydrologic modeling has provided new prospects for estimating daily continuous river discharge, which is particularly suited for poorly gauged or ungauged basins. In this study, we explored the possibility of calibrating a hydrologic model (CREST-RS) using Jason-2-derived water levels, followed by SWOT (the Surface Water and Ocean Topography mission)-like data (the combination of Landsat-derived at-a-section river widths and concurrent gauged water levels). Remotely sensed discharge that serves as the calibration reference was derived from two types of empirical formulas, which were designed specifically for water levels and the joint use of water levels and river widths, respectively. Subsequently, the simulated discharge was integrated with the remotely sensed counterpart to allow automatic calibration using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). Here, five scenarios were performed to explore the potential capability of satellite altimetry and the SWOT-like data in discharge estimation in the ungauged upper Brahmaputra River (UBR, scenarios I–III) and its tributary the Lhasa River (LR, scenarios IV–V). Results showed that model calibration using the Jason-2-derived water levels could provide reasonably well-constrained parameters for discharge estimation, with the Nash–Sutcliffe Efficiency coefficient (NSE) reaching 0.85 during 2003–2014. For the SWOT-like data, the NSE reached 0.85 for the UBR and 0.75 for the LR, respectively. This study highlights the potential of performing model calibration using satellite altimetry and SWOT-like observations, which paves the way to estimate river discharge for ungauged basins globally.