Enhancing U-Net-Based Super-Resolution Models for Real-Time Rainfall–Runoff Flood Simulation
DOI:
https://doi.org/10.26754/jji-i3a.202613396Resumen
Real-time flood forecasting requires efficient high-resolution simulations. We combine the TRITON hydrodynamic solver with U-Net-based super-resolution models trained on paired coarse–fine simulations. A sensitivity analysis of different loss functions is conducted to optimize reconstruction accuracy and flood extent prediction, achieving 4× spatial enhancement with centimeter-level errors under realistic rainfall events.
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Publicado
2026-07-17
Número
Sección
Artículos (Tecnologías Industriales)
Licencia
Derechos de autor 2026 Juan Manuel Pérez García de Carellán, Mario Morales Hernández, Pilar García Navarro

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
Cómo citar
Pérez García de Carellán, J. M., Morales Hernández, M., & García Navarro, P. (2026). Enhancing U-Net-Based Super-Resolution Models for Real-Time Rainfall–Runoff Flood Simulation. Jornada De Jóvenes Investigadores Del I3A, 14. https://doi.org/10.26754/jji-i3a.202613396
