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Machine Learning Utilization for Bed Load Transport in Gravel-Bed Rivers

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  • Vasileios Kitsikoudis
  • Epaminondas Sidiropoulos
  • Vlassios Hrissanthou

Abstract

Three data-driven techniques, namely artificial neural networks, adaptive-network-based fuzzy inference system, and symbolic regression based on genetic programming, are employed for the prediction of bed load transport rates in gravel-bed steep mountainous streams and rivers in Idaho (U.S.A.), and the potential of several input variables is investigated. The input combinations that were tested are based, mainly, on unit stream power, stream power, and shear stress, and exhibited similarly good performance, with respect to the machine learning technique used, accentuating the importance of the regression model. The derived models are robust, generalize very well in unseen data, and generated results superior to those of some of the widely used bed load formulae, without the need to set a threshold for the initiation of motion, and consequently avoid predicting erroneous zero transport rates. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Vasileios Kitsikoudis & Epaminondas Sidiropoulos & Vlassios Hrissanthou, 2014. "Machine Learning Utilization for Bed Load Transport in Gravel-Bed Rivers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3727-3743, September.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:11:p:3727-3743
    DOI: 10.1007/s11269-014-0706-z
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    References listed on IDEAS

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    1. Gokmen Tayfur & Yashar Karimi & Vijay Singh, 2013. "Principle Component Analysis in Conjuction with Data Driven Methods for Sediment Load Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2541-2554, May.
    2. Einstein, Hans Albert, 1950. "The Bed-Load Function for Sediment Transportation in Open Channel Flows," Technical Bulletins 156389, United States Department of Agriculture, Economic Research Service.
    3. H. Azamathulla & Robert Jarrett, 2013. "Use of Gene-Expression Programming to Estimate Manning’s Roughness Coefficient for High Gradient Streams," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 715-729, February.
    4. M. Mustafa & R. Rezaur & S. Saiedi & M. Isa, 2012. "River Suspended Sediment Prediction Using Various Multilayer Perceptron Neural Network Training Algorithms—A Case Study in Malaysia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(7), pages 1879-1897, May.
    5. M. Mustafa & R. Rezaur & S. Saiedi & M. Isa, 2012. "Erratum to: River Suspended Sediment Prediction Using Various Multilayer Perceptron Neural Network Training Algorithms—A Case Study in Malaysia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(7), pages 2123-2123, May.
    6. Aytac Guven & Özgür Kişi, 2011. "Estimation of Suspended Sediment Yield in Natural Rivers Using Machine-coded Linear Genetic Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(2), pages 691-704, January.
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    Cited by:

    1. Jenq-Tzong Shiau & Ting-Ju Chen, 2015. "Quantile Regression-Based Probabilistic Estimation Scheme for Daily and Annual Suspended Sediment Loads," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2805-2818, June.
    2. Isa Ebtehaj & Hossein Bonakdari, 2014. "Performance Evaluation of Adaptive Neural Fuzzy Inference System for Sediment Transport in Sewers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4765-4779, October.
    3. Ozgur Kisi & Coskun Ozkan, 2017. "A New Approach for Modeling Sediment-Discharge Relationship: Local Weighted Linear Regression," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 1-23, January.

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