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Estimation of suspended sediment load using three neural network algorithms in Ramganga River catchment of Ganga Basin, India

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Abstract

The information on suspended sediments of river is considered to be crucial for issues concerning water management and the environment. The abrupt quantity and nature of sediment loads can be best studied by simultaneously considering the governing variables contributing towards this physical phenomenon. Artificial Neural Network (ANN) is one of the suitable data-mining technique which helps in carrying out the modelling of this phenomenon. In this study, ANNs are employed to approximate the monthly mean suspended sediment load for Ramganga River. Three simulations with rainfall and water discharge data were carried out to predict the suspended sediment load. In terms of the selected performance criteria, three algorithms were evaluated and the results so obtained are presented. It has been found that rainfall values were not sufficient to correctly predict the suspended sediment load. However, considering water discharge values as input improves the performance of all the three considered algorithms.

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Acknowledgements

The author thankfully acknowledges the support provided by IIT Roorkee, India and Tsinghua University, Beijing, China. Author thanks the Council for Scientific and Industrial Research (CSIR), New Delhi, India for giving research fellowship. Central Water Commission, Lucknow, Government of India sympathetically gave the information important to the present work. The authors gratefully acknowledge the comments of the reviewers and the editor, which enormously improved the presentation of the manuscript.

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Authors and Affiliations

  1. Department of Earth Sciences, Indian Institute of Technology Roorkee, Roorkee, 247667, India

    Mohd Yawar Ali Khan

  2. Department of Mechanical Engineering, Z.H. College of Engineering and Technology, Aligarh Muslim University, Aligarh, 202002, India

    Faisal Hasan

  3. Department of Hydraulic Engineering, School of Civil Engineering, Institute of Hydrology and Water Resources, Tsinghua University, Beijing, 100084, China

    Mohd Yawar Ali Khan & Fuqiang Tian

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  1. Mohd Yawar Ali Khan
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Correspondence to Mohd Yawar Ali Khan.

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Khan, M.Y.A., Hasan, F. & Tian, F. Estimation of suspended sediment load using three neural network algorithms in Ramganga River catchment of Ganga Basin, India. Sustain. Water Resour. Manag. 5, 1115–1131 (2019). https://doi.org/10.1007/s40899-018-0288-7

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