Flood scenario spatio-temporal mapping via hydrological and hydrodynamic modelling and a remote sensing dataset: A case study of the Basento river (Southern Italy)

Today, hydrological and hydraulic modelling are essential tools for flood risk management, although these models are still affected by elements of uncertainty that needs to be reduced by optimizing their results. The present research aims to implement an operational mechanism on the Basento river basin in Southern Italy based on the cascading use of a physically based concentrated-parameter hydrological model for the estimation of flood hydrographs, and a twodimensional hydraulic model for flood mapping. The calibration of the hydrological model uses physical information to reduce the initial range of the set parameter values, and an automated optimisation procedure based on a genetic algorithm to find optimal values of the model parameters by comparing simulated and observed data for the 2013 flood event. To calibrate the hydraulic model, a series of flood maps extracted from multi-temporal SAR images was used. In addition, validation of the hydrological and hydraulic models was carried out on March 2011 flood event. The results show the reliability of the models during both calibration and validation, with the hydrological model achieving a Nash-Sutcliffe Efficiency coefficient between 0.86 and 0.91, and the hydraulic model leading to results with an accuracy close to 70 %. Considering the significance of the results, the developed modelling chain was used to simulate future event scenarios for risk management assessment and could operate as an early warning system.