Daily river discharge estimation using SWOT data

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. We develop a linear dynamic system that ingests SWOT observations for daily discharge estimation over continuous reaches in a single-branch river network to overcome this limitation. The linear dynamic system includes a process model based on a physically-based spatiotemporal discharge correlation model and observation equations utilizing SWOT products. We solve this dynamic system through a Kalman filter, which is executed in the time domain to obtain daily discharge. Building on the strong performance of the method with synthetic data, we apply this algorithm using SWOT measurements in the Rhine River, where we validate its performance by comparing the estimates against gauge discharge data. These efforts aim to unlock the potential of SWOT data for daily discharge estimation in diverse river networks globally.