In this work, the deep-learning FloodSformer model for inundation forecasting and the GPU-parallel hydrodynamic code PARFLOOD are applied to a real case study of breach-induced flooding, in orde rto compare the accuracy and computational performanc eof these alternative approaches for real-time forecasting.
Levee-Breach Inundation Forecasting with Deep-Learning and Hydrodynamic Models: The 2020 Panaro River Case Study / Dazzi, S., Vacondio, R., Pianforini, M.. - (2026), pp. 40570.521-40570.522. (16th International Conference on Hydroinformatics Zaragoza (Spain) 22-26 June 2026).
Levee-Breach Inundation Forecasting with Deep-Learning and Hydrodynamic Models: The 2020 Panaro River Case Study
Susanna Dazzi
;Renato Vacondio;Matteo Pianforini
2026-01-01
Abstract
In this work, the deep-learning FloodSformer model for inundation forecasting and the GPU-parallel hydrodynamic code PARFLOOD are applied to a real case study of breach-induced flooding, in orde rto compare the accuracy and computational performanc eof these alternative approaches for real-time forecasting.File in questo prodotto:
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