期刊
ENVIRONMENTAL MODELLING & SOFTWARE
卷 118, 期 -, 页码 172-186出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2019.04.010
关键词
Data mining; Digital elevation model; Hydrogeomorphology; Large-scale study; Supervised classification; Web application
类别
资金
- European Union's EU Framework Programme for Research and Innovation Horizon 2020 [676027]
- European Union
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.
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