Abstract
Nearly all formulations of conventional sediment load estimation method were developed based on a review of laboratory data or data field. This approach is generally limited by local so it is only suitable for a particular river typology. From previous studies, the amount of sediment load tends to be non-linear with respect to the hydraulic parameters and parameter that accompanies sediment. The dominant parameter is turbulence, whereas turbulence flow velocity vector direction of x, y and z. They were affected by water bodies in 3D morphology of the cross section of the vertical and horizontal. This study is conducted to address the non-linear nature of the hydraulic parameter data and sediment parameter against sediment load data by applying the artificial neural network (ANN) method. The method used is the backpropagation neural network (BPNN) schema. This scheme used for projecting the sediment load from the hydraulic parameter data and sediment parameters that used in the conventional estimation of sediment load. The results showed that the BPNN model performs reasonably well on the conventional calculation, indicated by the stability of correlation coefficient (R) and the mean square error (MSE).
Highlights
A number of researchers across the globe have developed various procedures and theory to predict sediment load
The existing theories have not been able to accurately predict the actual sediment load when implemented on particular rivers [3]
This study aims to demonstrate the non-linear properties of the hydraulic parameters data and sediment parameter with the sediment load measurement data
Summary
A number of researchers across the globe have developed various procedures and theory to predict sediment load. Formulations of bed load were first developed and introduced extensively by Du Boys (1879) with the concept of shear stress approach [1]. Several approaches were developed such as graphics solution, the concept of probability, stream power concepts and the methods of multimodal characteristics. The method that most frequently used by researchers is the regression method [2]. The existing theories have not been able to accurately predict the actual sediment load when implemented on particular rivers [3]. From various measurement data test through the sediment flume experiments in the laboratory and natural river measurement data, there are limitations in the application of available theories [4]. The results show that there is a big difference between the rates of sediment transport estimation with the sediment discharge measurement results
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