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

Viewed

Total article views: 2,169 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,588 523 58 2,169 150 26 26
  • HTML: 1,588
  • PDF: 523
  • XML: 58
  • Total: 2,169
  • Supplement: 150
  • BibTeX: 26
  • EndNote: 26
Views and downloads (calculated since 23 May 2022)
Cumulative views and downloads (calculated since 23 May 2022)

Viewed (geographical distribution)

Total article views: 2,169 (including HTML, PDF, and XML) Thereof 2,070 with geography defined and 99 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Apr 2024
Download
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.