A Physically Informed Transformation of Sentinel-1 SAR Observations for Streamflow Inference in Small and Complex Rivers

Accurate measurement of river discharge is central to flood risk management and water resources planning, operations and management. However, in data-scarce and information-restricted settings, including transboundary basins, satellite observations are widely used; nevertheless, consistent monitoring remains difficult for small and narrow rivers. Here we show that surface water dynamics observed by Sentinel-1 synthetic aperture radar (SAR) can be transformed into a hydrologically meaningful surrogate discharge signal, providing a reasonable estimation of streamflow without reliance on ground-based ancillary observations. We develop a scalable SAR-based framework that extracts temporally consistent surface water extent by combining adaptive thresholding with connectivity- and geometry-informed filtering, yielding a robust surrogate river discharge (SR) time series. Across 19 rivers selected across multiple continents (13 countries) spanning diverse hydroclimatic and geomorphic settings, SAR-derived SR exhibits strong and systematic relationships with observed streamflow, outperforming commonly used alternative surrogates particularly in small and complex river systems. As a downstream demonstration of hydrological utility, when integrated into a parsimonious rainfall–runoff model using satellite-derived precipitation and evapotranspiration, the SAR-based SR can help constrain physically defensible, continuous streamflow simulations, a desired necessity in data-scarce basins. Our results demonstrate when and where SAR observations can reliably inform river flow dynamics, highlighting both the potential and the limitations of surface water extent–based discharge inference for ungauged settings.