A web application for hydrogeomorphic flood hazard mapping. (August 2019)

• Record Type: Journal Article
• Authors: Tavares da Costa, Ricardo; Manfreda, Salvatore; Luzzi, Valerio; Samela, Caterina; Mazzoli, Paolo; Castellarin, Attilio; Bagli, Stefano
• Is Part Of: Environmental modelling & software. Volume 118(2019)
• Page Start: 172
• Page End: 186
• Publication Date: 2019-08
• Subjects: Data mining -- Digital elevation model -- Hydrogeomorphology -- Large-scale study -- Supervised classification -- Web application; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2019.04.010
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: A detailed delineation of flood-prone areas over large regions represents a challenge that cannot be easily solved with today's resources. The main limitations lie in algorithms and hardware, but also costs, scarcity and sparsity of data and our incomplete knowledge of how inundation events occur in different river floodplains. We showcase the implementation of a data-driven web application for regional analyses and detailed (i.e., tens of meters) mapping of floodplains, based on (a) the synthesis of hydrogeomorphic features into a morphological descriptor and (b) its classification to delineate flood-prone areas. We analysed the skill of the descriptor and the performance of the mapping method for European rivers. The web application can be effectively used for delineating flood-prone areas, reproducing the reference flood maps with a classification skill of 88.59% for the 270 major river basins analysed across Europe and 84.23% for the 64 sub-catchments of the Po River. Highlights: Progress in hydrogeomorphic flood hazard mapping is presented. A cloud-based web application for data-driven hydrogeomorphic flood hazard mapping is implemented. The GFI classifier displayed strong discerning capabilities for mapping flood-prone areas in Europe. Flood-prone areas for the whole Europe are computed and evaluated for different return periods using the proposed web application.