Articles | Volume 11, issue 4
https://doi.org/10.5194/esurf-11-681-2023
https://doi.org/10.5194/esurf-11-681-2023
Research article
 | 
27 Jul 2023
Research article |  | 27 Jul 2023

Development of a machine learning model for river bed load

Hossein Hosseiny, Claire C. Masteller, Jedidiah E. Dale, and Colin B. Phillips

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Cited articles

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Barry, J. J., Buffington, J. M., Goodwin, P., King, J. G., and Emmett, W. W.: Performance of Bed-Load Transport Equations Relative to Geomorphic Significance: Predicting Effective Discharge and Its Transport Rate, Hydraul. Eng., 134, 601–615, 2008. 
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Short summary
It is of great importance to engineers and geomorphologists to predict the rate of bed load in rivers. In this contribution, we used a large dataset of measured data and developed an artificial neural network (ANN), a machine learning algorithm, for bed load prediction. The ANN model predicted the bed load flux close to measured values and better than the ones obtained from four standard bed load models with varying degrees of complexity.