Articles | Volume 20, issue 12
Research article
19 Dec 2016
Research article |  | 19 Dec 2016

Calibration of channel depth and friction parameters in the LISFLOOD-FP hydraulic model using medium-resolution SAR data and identifiability techniques

Melissa Wood, Renaud Hostache, Jeffrey Neal, Thorsten Wagener, Laura Giustarini, Marco Chini, Giovani Corato, Patrick Matgen, and Paul Bates

Abstract. 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 simultaneously calibrate the bankfull channel depth and channel roughness parameters within a 2-D LISFLOOD-FP hydraulic model using an archive of moderate-resolution (150 m) ENVISAT satellite SAR-derived flood extent maps and a binary performance measure for a 30 × 50 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 dynamic identifiability analysis (DYNIA) (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 the peak of the flood hydrograph, and improves when more images are combined. We found that 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 2-D hydraulic model.

Short summary
We propose a methodology to calibrate the bankfull channel depth and roughness parameters in a 2-D hydraulic model using an archive of medium-resolution SAR satellite-derived flood extent maps. We used an identifiability methodology to locate the parameters and suggest the SAR images which could be optimally used for model calibration. We found that SAR images acquired around the flood peak provide best calibration potential for the depth parameter, improving when SAR images are combined.