Single satellite Synthetic Aperture Radar (SAR) data are now regularly used to estimate hydraulic model parameters such as channel roughness, depth and water slope. However despite channel geometry being critical to the application of hydraulic models and poorly known a priori, it is not frequently the object of calibration. This paper presents a unique method to calibrate simultaneously the bankfull channel depth and channel roughness parameters within a 2D LISFLOOD-FP hydraulic model using an archive of moderate (150 m) resolution ENVISAT satellite SAR-derived flood extent maps and a binary performance measure for a 30x50 km domain covering the confluence of the rivers Severn and Avon in the UK. The unknown channel parameters are located by a novel technique utilising the Information Content and DYNIA identifiability (Wagener et al. 2003) of single and combinations of SAR flood extent maps to find the optimum satellite images for model calibration. Highest Information Content is found in those SAR flood maps acquired near to the peak of the flood hydrograph, and improves when more images are combined. We found model sensitivity to variation in channel depth is greater than for channel roughness and a successful calibration for depth could only be obtained when channel roughness values were confined to a plausible range. The calibrated reach-average channel depth was within 0.9 m (16% error) of the equivalent value determined from river cross section survey data, demonstrating that a series of moderate resolution SAR data can be used to successfully calibrate the depth parameters of a 2D hydraulic model.