Prediction of Sediment Load Concentration in Rivers using Artificial Neural Network Model |
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Authors: | H M Nagy K Watanabe M Hirano |
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Affiliation: | 1PhD, Associate Professor, Dept. of Civil Engineering, Alexandria Univ., Alexandria, Egypt. 2Dr. of Engineering, Professor, Dept. of Civil Engineering, Saga Univ. Saga 840, Japan. 3Dr. of Engineering, Professor Emeritus, Kyushu Univ. Fukuoka 812, Japan.
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Abstract: | An artificial neural model is used to estimate the natural sediment discharge in rivers in terms of sediment concentration. This is achieved by training the network to extrapolate several natural streams data collected from reliable sources. The selection of water and sediment variables used in the model is based on the prior knowledge of the conventional analyses, based on the dynamic laws of flow and sediment. Choosing an appropriate neural network structure and providing field data to that network for training purpose are addressed by using a constructive back-propagation algorithm. The model parameters, as well as fluvial variables, are extensively investigated in order to get the most accurate results. In verification, the estimated sediment concentration values agree well with the measured ones. The model is evaluated by applying it to other groups of data from different rivers. In general, the new approach gives better results compared to several commonly used formulas of sediment discharge. |
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Keywords: | Sediment transport Rivers Neural networks Sediment discharge |
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