Deep learning-based algorithms for long-term prediction of chlorophyll-a in catchment streams

•We developed a deep learning-based framework for long-term Chl-a simulation.•The performance of six state of the art deep learning algorithms was compared.•Our study employed separate sub-basins to train and evaluate DL models.•Chl-a prediction is improved by using sub-basin characteristics as inpu...

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Bibliographic Details
Published in:Journal of hydrology (Amsterdam) Vol. 626; p. 130240
Main Authors: Abbas, Ather, Park, Minji, Baek, Sang-Soo, Cho, Kyung Hwa
Format: Journal Article
Language:English
Published: Elsevier B.V 01.11.2023
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ISSN:0022-1694, 1879-2707
Online Access:Get full text
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