GIS automation of large-scale flood vulnerability analysis for drainage basins, based on a single Digital Elevation Model

In the context of climate change, probability of risk phenomena occurrence is more frequent and with greater intensity. This is especially valid for floods which cause significantly more damage and casualties, as flood-inducing conditions are met more often. The risk is emphasized by the fact that countless human settlements are located on the floodplain of river courses of different sizes and flow rates. The current study aims to detail an automatic GIS model that can easily compare drainage sub-basins of similar order, according to Horton-Strahler hierarchical classification, at large scale, for a given basin, based on morphometric parameters. This implies the use of a digital elevation model (DEM) as the only input layer, and setting a few parameters, in order to extract several quantifiable hydrological indicators, relevant to flood analysis. Some of the most relevant ones from the list are the elongation ratio, circularity ratio, relief ratio, roughness number, drainage density etc. All the functions have been integrated into a GIS tool, that would automatically aid in the fast creation of a final vector layer, that discerns between drainage basins with higher and lower degrees of relative vulnerability. This layer contains an attribute table with all the relevant parameters, as well as the result of the formula that assigns flood vulnerability values to each drainage basin, making possible the quantitative comparison between all the drainage sub-basins. The resulting table analysis is conducted in the background, based on the calculation of normalized values for each parameter, which are encompassed into a final vulnerability score. The model is easily applicable to most types of raster elevation layers, as long as they are in a projected coordinate system, regardless of pixel size. Furthermore, several functions were added to the model to mitigate potential errors that can occur in isolated cases, where the topography is particularly difficult to interpret by some native GIS tools. Therefore, this model is an easy to apply tool, that automatically identifies more vulnerable sub-basins, from a large drainage basin, over extended areas, with limited user-input, facilitating decision making in flood management, while providing quantifiable flood vulnerability results, in a very short period of time, without requiring extensive knowledge from the user.