Sedimentation in sewer pipes has negative impact on the performance of sewerage systems. However, due to complex nature of sedimentation; determining governing equations is difficult and the results of the available classic models for computing bedload transport rate often differ from each other. This paper focuses on the capability of support vector machine (SVM) as a Meta-model approach for predicting bedload transport in pipes. The method was applied for the deposition and limit of deposition states of sediment transport. Two different scenarios were proposed; in the Scenario 1, the input combinations were prepared using only hydraulic characteristics, on the other hand, Scenario 2 was built using both hydraulic and sediment characteristics as model inputs of bedload transport. A comparison between SVM and employed classic approaches in predicting the sediment transport indicated the supreme performance of the SVM in which more accurate results were obtained. Also it was found that for estimation bedload transport in pipes, Scenario 2 led to more valid outcome than Scenario 1. Based on the sensitivity analysis, parameters Frm and d50/y in limit of deposition state and Frm in deposition state had the more dominant role in prediction bedload discharge in pipes than other parameters.
- bedload discharge
- support vector machine (SVM)
- First received 17 April 2016.
- Accepted in revised form 5 September 2016.
- © IWA Publishing 2016