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.
Machine-learning and physics-based numerical modelling for flood level forecasting in rivers: insights from a case study in Italy / Dazzi, Susanna; Ferrari, Alessia; Mignosa, Paolo. - (2022), pp. 357-358. (Intervento presentato al convegno 7th IAHR Europe Congress tenutosi a Atene nel 7-9 Settembre 2022).
Machine-learning and physics-based numerical modelling for flood level forecasting in rivers: insights from a case study in Italy
Susanna DAZZI;Alessia FERRARI;Paolo MIGNOSA
2022-01-01
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.File in questo prodotto:
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