A multimesh graph-neural-network surrogate conditioned on discharge and trained with pushforward produces accurate 6-hour flood forecasts in 0.4 s on GPU versus 180 min on 56 CPU cores for the reference Telemac2D model.
Multi-scale hydraulic graph neural networks for flood modelling
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Toward an Operational GNN-Based Multimesh Surrogate for Fast Flood Forecasting
A multimesh graph-neural-network surrogate conditioned on discharge and trained with pushforward produces accurate 6-hour flood forecasts in 0.4 s on GPU versus 180 min on 56 CPU cores for the reference Telemac2D model.