Deriving stage-discharge-sediment concentration relationships using fuzzy logic

Many practical problems in water resources require knowledge of the sediment load carried by the rivers, or of the load the rivers can carry without danger of aggragadation or degradation. Hence, the measurement of sediments being transported by a river is of vital interest for planning and designing of various water resources projects. The conventional methods available for sediment load estimation are largely empirical, with sediment rating curves being the most widely used. The rating relationships baked on regression techniques are generally not adequate in view of the inherent complexity of the problem. In this Study, a fuzzy logic technique is applied to model the stage-discharge-sediment concentration relationship. The technique has been applied to two gauging sites in the Narmada basin in India. Performance of the conventional sediment rating curves, neural networks and fuzzy rule-based models was evaluated using the coefficient of correlation, root mean square error and pooled average relative (underestimation and overestimation) errors (PARE) of sediment concentration. Comparison of results showed that the fuzzy rule-based model could be successfully applied for sediment concentration prediction as it significantly improves the magnitude of prediction accuracy.