GFPLAIN250m dataset: Mapping the extent of Earth's Floodplains using a geomorphic approach

Increasing land development and changing population distributions worldwide constitute a challenge determining more pressure on resource-rich coastal and fluvial corridors that are, nowadays, among the most endangered areas. Identifying the extent of floodplains is, thus, of paramount importance for earth, environmental and socioeconomic studies addressing natural and urban ecosystem resource and risk management issues. This research presents the first comprehensive and homogeneous high-resolution gridded dataset of Earth's floodplains at 250-m resolution (GFPLAIN250m). The global floodplain dataset is produced by processing elevation data by means of a fast geospatial data processing tool, the GFPLAIN algorithm, that can produce continental floodplain maps in minutes. GFPLAIN is a geomorphic floodplain delineation algorithm analyzing river basin morphology to recognize the floodplain as that unique landscape feature shaped by the accumulated effect of erosion and deposition processes occurring over time with specific regard to most extreme flooding events that leave a clear trace along fluvial buffers. The GFPLAIN algorithm is, thus, based on the principle that Digital Terrain Models (DTMs) implicitly contain the floodplain extent information. The Shuttle Radar Topography Mission (SRTM) DTM is used as main input of the Open Source GFPLAIN algorithm (https://github.com/fnardi/GFPLAIN ) to produce the GFPLAIN250m dataset (https://doi.org/10.6084/m9.figshare.6665165.v1 ). The release of GFPLAIN algorithm and dataset paves the way to many potential multi-disciplinary applications including flood hazard management, habitat restoration, urban planning and land development studies, and the analysis of human-flood interaction among others. The validation and performances of the GFPLAIN250m dataset are presented with a large scale consistency analysis comparing the geomorphic floodplain delineations as respect to flood hazard modelling studies at the global scale.