Machine-learning and physics-based numerical modelling for flood level forecasting in rivers: insights from a case study in Italy

Abstract

This paper considers the case study of the Parma River (Italy) to highlight drawbacks in data-driven methods for flood forecasting, in particular their limited flexibility in accounting for possible modifications in the river geometry or roughness, in comparison with physics-based models, which can be updated quite easily