 This paper proposes a new approach to incorporating synthetic aperture radar, SAR, data into hydrological models for improved flood prediction. The authors used a particle filter algorithm to assimilate SAR data into a coupled hydrologic hydraulic model. They tested their methodology on a river reach in Luxembourg and found that the particle filter algorithm significantly reduced uncertainty in water level and discharge predictions. Additionally, they found that updating the model's storage and forcing variables was not sufficient. Instead, they also needed to update the model's state variables. Finally, they concluded that the proposed methodology could be used to provide reliable and timely SAR-based flood monitoring services. This article was authored by PMATGEN, M-montenary, our hostake, and others.