Simulación del caudal en España utilizando redes neuronales Long Short-Term Memory
Enviado: 24-11-2025
|Aceptado: 12-01-2026
|Publicado: 30-01-2026
Derechos de autor 2026 Ingeniería del Agua
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
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Palabras clave:
CAMELS-ES, CARAVAN, EFAS, LISFLOOD, LSTM
Agencias de apoyo:
Resumen:
Dentro de la iniciativa CARAVAN, que pretende crear un conjunto de datos hidrológicos globales, se ha creado el subconjunto de datos CAMELS-ES correspondiente a España. Este conjunto de datos contiene las series de caudal diario del Anuario de Aforos de España en 269 cuencas, así como series meteorológicas y características de las cuencas. A partir de estos datos se han entrenado dos redes neuronales LSTM (Long Short-Term Memory). La primera red se entrenó para simular el caudal observado en las cuencas, mientras que la segunda red se entrenó como un emulador del modelo hidrológico físicamente basado LISFLOOD-OS. Los resultados de la primera de estas redes muestran el potencial de este tipo de modelos de aprendizaje profundo, con un rendimiento superior (KGE 0.69) al mostrado por LISFLOOD-OS (KGE 0.38). En cambio, el rendimiento de la segunda red indica que son necesarios mayores esfuerzos para conseguir un emulador del modelo LISFLOOD-OS.
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