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Prediction of daily suspended sediment load using wavelet and neurofuzzy combined model

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Abstract

This study investigated the prediction of suspended sediment load in a gauging station in the USA by neuro-fuzzy, conjunction of wavelet analysis and neuro-fuzzy as well as conventional sediment rating curve models. In the proposed wavelet analysis and neuro-fuzzy model, observed time series of river discharge and suspended sediment load were decomposed at different scales by wavelet analysis. Then, total effective time series of discharge and suspended sediment load were imposed as inputs to the neuro-fuzzy model for prediction of suspended sediment load in one day ahead. Results showed that the wavelet analysis and neuro-fuzzy model performance was better in prediction rather than the neuro-fuzzy and sediment rating curve models. The wavelet analysis and neuro-fuzzy model produced reasonable predictions for the extreme values. Furthermore, the cumulative suspended sediment load estimated by this technique was closer to the actual data than the others one. Also, the model could be employed to simulate hysteresis phenomenon, while sediment rating curve method is incapable in this event.

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Authors and Affiliations

  1. Department of Civil Engineering, K.N. Toosi University of Technology, Tehran, Iran

    T. Rajaee Ph.D. & S. A. Mirbagheri Ph.D. (Associate Professor)

  2. Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran

    V. Nourani Ph.D. (Associate Professor)

  3. Deptartment of Civil Engineering, University of Qom, Qom, Iran

    A. Alikhani Ph.D. (Assistant Professor)

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  1. T. Rajaee Ph.D.
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  2. S. A. Mirbagheri Ph.D.
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  3. V. Nourani Ph.D.
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  4. A. Alikhani Ph.D.
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Correspondence to S. A. Mirbagheri Ph.D..

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Rajaee, T., Mirbagheri, S.A., Nourani, V. et al. Prediction of daily suspended sediment load using wavelet and neurofuzzy combined model. Int. J. Environ. Sci. Technol. 7, 93–110 (2010). https://doi.org/10.1007/BF03326121

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  • DOI: https://doi.org/10.1007/BF03326121

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