Flash-flood hazard using deep learning based on H2O R package and fuzzy-multicriteria decision-making analysis

•Flash-flood susceptibility modeling was done using highly accurate models.•A number of 111 flash-flood locations were used for modelling.•A number of 8 flash-flood predictors were used to estimate the susceptibility.•DLNN-AHP was the most performant machine learning model.•Flash-flood susceptibility maps achieved a very good prediction accuracy.