ABSTRACT
Most studies focusing on flood analysis have implemented various types of runoff models at different scales. Regardless of the nature of each one, all these models attempt to identify areas susceptible for flooding after an event of severe precipitation. Mapping the flood susceptibility helps understand the spatial trends of flooding as well as organize efficient planning and flood prevention. In this chapter, a new index for mapping the susceptibility of flooding is introduced. This index is called the Flood Susceptibility Index (FSI) and is based on the use of remote sensing (RS) data, Geographic Information System (GIS) modeling, and statistical analysis. The implementation of this method involves steps such as spatial database creation (with the flood-related factors and categorization of these factors), flooded areas extraction (by using RS datasets and analysis), calculation of the number of flooded areas for each factor category (by using GIS techniques), FSI estimation for each category, and finally integration of FSI values to calculate total FSI in the area under investigation. This approach was used to produce flood susceptibility maps of Sperchios River basin, in Central Greece. The flood inventory was extracted from RS imagery. Afterward, the flood inventory was split into a testing dataset: 70% for training the FSI model and the remaining 30% for validation. The factors that were implemented in the proposed analysis include slope, land cover, hydrolithology, flow accumulation, flow length, distance from main river network, and distance from coastline. The accuracy was found to be 96.5%, indicating an excellent prediction capability for the proposed model.
The contribution of this study is that even though it is tested on a basin with specific characteristics, it can be applied to all types of river basins, torrents, and catchments. This also means that besides the characteristics of the study area, this methodology can be applied on a variety of scales (local, regional, and so on). Furthermore, the FSI may support policy making by identifying the flood-susceptible areas and thus by becoming a useful tool for implementing the proper precaution measures, constructing the necessary works, and managing adequately, in general, the risk areas.
Key words: Floods; remote sensing; GIS; Flood Susceptibility Index
