Mirko Barada

Estuaries are among most vulnerable parts of our planet in terms of flood risk because they are constantly exposed to flood sources from at least two directions. While different flood modelling tools are helping us to be better prepared for flood events, state-of-the-art space technologies are providing useful high resolution (temporal and spatial) data to quantify and monitor real flood impacts and consequences, regardless of night and cloudiness.In this study we are: a) applying LISFLOOD-FP hydrodynamic model for modelling compound flood event in the Dyfi estuary, Wales (UK) and b) using Sentinel-1 SAR data to map flood event from the same period and to validate flood inundation model. The selected flood event (> 300 m3/s and around 70 cm surge) caused large flooding along the estuary, particularly in the upper parts. Modelled results are shown as water surface elevation and water depth classified raster maps, which are used later for comparison with the SAR image.Raw Sentinel-1 SAR (GRD) image downloaded from Copernicus Browser had to be pre-processed in ArcGIS PRO (The Synthetic Aperture Radar toolset) to remove unwanted noise and correct distortions. Further, RGB color composite was produced from the calibrated SAR image and used for extracting water bodies/flooded areas. It was achieved by applying deep learning tools integrated in ArcGIS PRO which classify pixels (wet/dry) based on a previously trained sample. Resulting raster was then compared with the modelled flood extent, quantifying the differences. Matching was very good in the upper parts where major flooding was recorded (> 80 % agreement), while the model was slightly less accurate in the lower estuary and along the salt marsh zone due to larger DEM uncertainty in those areas. However, when selected shallow areas (e.g. 0-1 cm or 0-2 cm class) were removed from the model, matching between modelled and observed flood extent was higher.

Floods are a constant threat to communities within and around estuaries worldwide. This is because several drivers may occur there at the same time which leads to the compound flooding (e.g. high river discharge + storm surge). In this study LISFLOOD-FP hydrodynamic model is applied to examine the efficiency of different management strategies on flooding in the Dyfi Estuary, in Mid Wales. Five different bathymetries, including the current one, were developed in ArcGIS and included in the analysis: a) “hold the line”, b) “remove the line”, c) “advance the line”, d) “retreat the line”, e) “breach in the line”. Modified November 2020 compound flood event boundary conditions were forced from the coast and from the Dyfi bridge. Model results shown, among other things, that nature-based solutions in the lower estuary, represented by salt marshes and floodplain restoration measures, have a great potential in reducing water elevations across the estuary, unlike the advance the line scenario or the current bathymetry.Additionally, results obtained from different management scenarios are analyzed and compared against results from the selected design storm events. These events were based on modifying parameters such as 1) relative timing of flood peaks, 2) storm duration and 3) climate change sensitivity (SLR and increase in discharge) which provided set of different compound flood events that were forced by LISFLOOD, in combination with the current estuary shape, unlike when modelling different management scenarios. This approach enabled us to perform an effective comparative analysis which addressed the key hypothesis of the research stating that changes in estuary shape will have bigger effect on flooding than changes in flood event itself. Indeed, it is shown that variability in water elevations caused by different management scenarios is bigger compared to variability caused by changing the boundary conditions only, although not always leading to higher water elevations along the estuary.