Mohammad J. Tourian (Institute of Geodesy, University of Stuttgart, Germany); Pierre-Olivier Malaterre (INRAE, UMR G-eau, Montpellier, France); Colin Gleason (Department of Civil and Environmental Engineering, University of Massachusetts Amherst, Amherst, USA); Michael Durand (School of Earth Sciences, Ohio State University, Columbus, USA)

The SWOT satellite mission is the first to conduct a global survey of the Earth's surface waters, measuring water surface height, river width, and water surface slope, based on which river discharge is estimated. At mid-latitudes, the repeat orbit design of SWOT only allows a sampling of twice per repeat cycle, which is considered too low for most hydrological applications. To address the spatiotemporal limitations of SWOT, we develop a method, based on a Kalman Filter, that assimilates SWOT observations across continuous reaches within a single-branch river network to obtain daily discharge estimates. The Kalman filter solves a linear dynamic system, which includes a process model based on a physically based spatiotemporal discharge correlation model and observation equations that utilize SWOT products. Our test analysis over the Rhine River shows that the estimated discharge reaches a median correlation of 0.70, a median NSE of 0.46, and a median rRMSE of 18% when using the MOMMA discharge product, whereas with the SIC4DVar product, the correlation remains the same, but the NSE drops to 0.32 and the rRMSE increases to 22%. For the Science Team meeting presentation, we plan to apply the method to multiple rivers in the SWOT development set (Devset) using real SWOT measurements. Devset is a set of reaches defined within the SWOT Discharge Algorithm Working Group for calibration and validation. To further enhance our method and improve the accuracy of the discharge estimates, we also consider incorporating other satellite-based discharge products.