Spatial Evaluation of a Natural Flood Management Project Using SAR Change Detection

This study proposes an evaluation method using C-band Sentinel-1 synthetic aperture radar (SAR) data to provide evidence of flood characteristic changes after the restoration of a floodplain. A portable, flexible evaluation framework has replicated previous change detection research approaches to analyse a Natural Flood Management (NFM) project on the Sussex Ouse river in southern England, conducted by the Sussex Flow Initiative (SFI), to ascertain how control measures have helped mitigate flood risk. GIS operations were conducted on the mapped results of the change detection procedure to identify how flood area, form and compactness have been affected after the NFM installation restored a floodplain to slow river flow and how these changes relate to the overall aims of the project. Innovative means were employed to verify the change detection methodology by sampling flood records from internet-published drone footage. The overall accuracy achieved using the Change Detection and Thresholding (CDAT) technique was 75%. The use of SAR data provides evidence of how NFM features function during significant flood events, providing a mapped delineation of the actual flood extent. A comprehensive scorecard has been developed to evaluate the positive and negative outcomes of the spatial changes that have manifested in post-restoration floods, in comparison to inundation before the installation. Results from this study have been included in the annual report of the SFI project to demonstrate how key features have attenuated flood waters in accordance with design intentions.

Automated summary

This study proposes an evaluation method using C-band Sentinel-1 synthetic aperture radar (SAR) data to provide evidence of flood characteristic changes after the restoration of a floodplain. The evaluation framework replicates previous change detection research approaches and analyses the effects of Natural Flood Management (NFM) measures on flood risk mitigation. The study verifies the change detection methodology using flood records from drone footage and achieves an overall accuracy of 75% using the Change Detection and Thresholding (CDAT) technique. The use of SAR data maps the actual flood extent and evaluates the positive and negative outcomes of post-restoration floods.