Untangling hybrid hydrological models with explainable artificial intelligence
Hydrological models are valuable tools for developing streamflow predictions in unmonitored catchments to increase our understanding of hydrological processes. A recent effort has been made in the development of hybrid (conceptual/machine learning) models that can preserve some of the hydrological p...
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Autores principales: | Daniel Althoff, Helizani Couto Bazame, Jessica Garcia Nascimento |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
IWA Publishing
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/1fa6d8abbab3463a85b7d216edde8b9f |
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