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The annual sediment load of a river is generally determined either from direct measurements of the sediment load throughout the year or from any of the many sediment transport equations that are available today. Due to lack of a long-term sediment concentration data, sediment rating curves and flux estimation are the most widely applied. This paper has investigated the abilities of statistical models to improve the accuracy of streamflow-suspended sediment relationships in daily and annual suspended sediment estimation. In this study, a comparison was made between suspended sediment rating curves and artificial neural networks (ANNs) for the El Kebir catchment. Daily water discharge and daily suspended sediment data from the gauging station of Ain Assel, were used as inputs and targets in the models which were based on the cascade-forward and feed-forward back-propagation using Levenberg-Marquardt and Bayesian regularization algorithms. The model results have shown that the ANN models have the highest efficiency to reproduce the daily sediment load and the global annual sediment yields. Our estimation based on the available data indicated that the areas along the El Kebir River have experienced high sediment fluxes that could have obvious impacts on the sediment trapping and siltation in the Mexa reservoir.

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Khanchoul, K. and Jansson, M.B., 2008: Sediment rating curves developed on stage and seasonal means in discharge classes for the Mellah wadi, Algeria. Geogr. Ann., 90 A (3): 227-236.ABSTRACT. The focus of the present study was to estimate suspended sediment load from the Mellah catchment (550 km 2 ) during storms. Suspended sediment rating curves were developed on data from a 23-year period. The regression technique of this paper involves a division of data into dischargebased classes, the mean concentrations and discharges of which are used to develop power regressions through log-transformation. Sediment rating curves were also developed on means of data grouped into seasons and stages. Sediment loads estimated by rating curves uncorrected for bias involved underestimations of down to 9% compared with loads from measured concentrations. Correction for bias reduced underestimations to a range from 0.79 to 3%. Rating curves divided into rising and falling stages had the lowest underestimation and were used to estimate load during periods without concentration measurements. During the 23-year study period, the mean annual suspended sediment yield was 373 T/ km 2 . Sediment transport is dominated by winter storms accounting for 61% of the annual load. A high exponent 'b' of the power regression equations during the winter season confirms the intense geomorphic work by winter season storms caused by high intensity rainfall, low vegetation cover, and heavy machine activity in the fields.

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