We present Flood-SHE, a data-driven, statistically-based procedure for the delineation of areas expected to be inundated by river floods. We applied Flood-SHE in the 23 River Basin Authorities (RBAs) in Italy using information on the presence or absence of inundations obtained from existing flood zonings as the dependent variable, and six hydro-morphometric variables computed from a 10 m × 10 m DEM as covariates. We trained 96 models for each RBA using 32 combinations of the hydro-morphometric covariates for the three return periods, for a total of 2208 models, which we validated using 32 model sets for each of the covariate combinations and return periods, for a total of 3072 validation models.
View Article and Find Full Text PDFInformation on historical landslides and floods - collectively called "geo-hydrological hazards - is key to understand the complex dynamics of the events, to estimate the temporal and spatial frequency of damaging events, and to quantify their impact. A number of databases on geo-hydrological hazards and their consequences have been developed worldwide at different geographical and temporal scales. Of the few available database structures that can handle information on both landslides and floods some are outdated and others were not designed to store, organize, and manage information on single phenomena or on the type and monetary value of the damages and the remediation actions.
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