Evaluation and interpretation of convolutional long short-term memory networks for regional hydrological modelling

Deep learning has emerged as a useful tool across geoscience disciplines; however, there remain outstanding questions regarding the suitability of unexplored model architectures and how to interpret model learning for regional-scale hydrological modelling. Here we use a convolutional long short-term...

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Bibliographic Details
Published in:Hydrology and Earth System Sciences
Main Authors: S. Anderson, V. Radić
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2022
Subjects:
geo
Online Access:https://doi.org/10.5194/hess-26-795-2022
https://hess.copernicus.org/articles/26/795/2022/hess-26-795-2022.pdf
https://doaj.org/article/604a66feea3845f5bd8820a2b4aac148