The Cryosphere
The Cryosphere
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Articles | Volume 16, issue 4
Articles | Volume 16, issue 4
https://doi.org/10.5194/tc-16-1447-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-1447-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 4
Research article
 | 
22 Apr 2022
Research article |  | 22 Apr 2022

Convolutional neural network and long short-term memory models for ice-jam predictions

Fatemehalsadat Madaeni, Karem Chokmani, Rachid Lhissou, Saeid Homayouni​​​​​​​, Yves Gauthier, and Simon Tolszczuk-Leclerc

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Short summary
We developed three deep learning models (CNN, LSTM, and combined CN-LSTM networks) to predict breakup ice-jam events to be used as an early warning system of possible flooding in rivers. In the models, we used hydro-meteorological data associated with breakup ice jams. The models show excellent performance, and the main finding is that the CN-LSTM model is superior to the CNN-only and LSTM-only networks in both training and generalization accuracy.
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