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  • Estuarine flood modelling using artificial neural networks

    Author(s)
    Fazel, Seyyed Adel Alavi
    Blumenstein, Michael
    Mirfenderesk, Hamid
    Tomlinson, Rodger
    Griffith University Author(s)
    Tomlinson, Rodger B.
    Year published
    2014
    Metadata
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    Abstract
    Prediction of water levels at estuaries poses a significant challenge for modelling of floods due to the influence of tidal effects. In this study, a two-stage forecasting system is proposed. In the first stage, the tidal portion of the available records is used to develop a tidal prediction system. The predictions of the first stage are used for flood modelling in the second. Experimental results suggest that the proposed flood modelling approach is advantageous for forecasting flood levels with more than 1 hour lead times.Prediction of water levels at estuaries poses a significant challenge for modelling of floods due to the influence of tidal effects. In this study, a two-stage forecasting system is proposed. In the first stage, the tidal portion of the available records is used to develop a tidal prediction system. The predictions of the first stage are used for flood modelling in the second. Experimental results suggest that the proposed flood modelling approach is advantageous for forecasting flood levels with more than 1 hour lead times.
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    Conference Title
    PROCEEDINGS OF THE 2014 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
    DOI
    https://doi.org/10.1109/IJCNN.2014.6889704
    Subject
    Other environmental sciences not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/157503
    Collection
    • Conference outputs

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