Deep learning for cross-region streamflow and flood forecasting at a global scale

Deep learning for cross-region streamflow and flood forecasting at a global scale

Streamflow and flood forecasting remains one of the long-standing challenges in hydrology. Traditional physically based models are hampered by sparse parameters and complex calibration procedures particularly in ungauged catchments. We propose a novel hybrid deep learning model termed encoder-decode...

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Bibliographic Details
Main Authors: Binlan Zhang, Chaojun Ouyang, Peng Cui, Qingsong Xu, Dongpo Wang, Fei Zhang, Zhong Li, Linfeng Fan, Marco Lovati, Yanling Liu, Qianqian Zhang
Format: Article
Language:English
Published: Elsevier 2024-05-01
Series:The Innovation
Subjects:
deep learning
hydrology
encoder-decoder double-layer LSTM
ED-DLSTM
streamflow forecasting
hydrological regionalization
Online Access:http://www.sciencedirect.com/science/article/pii/S2666675824000559

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http://www.sciencedirect.com/science/article/pii/S2666675824000559

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