A simplified method for water depth mapping over crops during flood based on Copernicus and DTM open data

After an extreme rainy event agricultural fields can be submerged by water. Stagnant water can be generated by river’ flooding or by soil saturation causing different damage level to crops. In this work, the flood event occurred on 3rd October 2020 in NW Italy along the Sesia river was assessed with special concern about damages affecting rice crop fields. A method was proposed aimed at detecting flooded areas and giving an estimate of water depth (WD) based on free available Copernicus data (Sentinel-1 and Sentinel-2) and digital terrain model (DTM). In particular, Sentinel-1 pre- and post-event images were compared by differencing (ΔVV). ΔVV was processed at pixel level to detect submerged areas through the thresholding Otsu's method. A simplified morphological analysis was then performed by DTM tessellation to map WD. A further step aimed at classifying submerged areas was achieved based on DTM and a proximity analysis, making possible to separate areas where water was related to soil saturation from areas where water was coming from the river. Corine Land Cover 2018 level-3 and NDVI from a Sentinel-2 pre-event image were used to map crops that were still to be harvested at the time of flood. These were the ones that were considered while estimating the potential economic loss. A total of 255 ha of rice that still to be harvested were submerged but only 211 ha were affected by river overflow. Using local rice yield and price the resulting economic loss was about 2,200,000 €.