Suspended Sediment Estimation Of Skunk River In Usa Using Fuzzy Logic Model
Estimation of sediment concentration in a river is very important for many water resources projects. Conventional methods such as sediment rating curves, are not able to provide sufficiently accurate results. In this study, two models: Sediment Rating Curve (SRC) and Fuzzy Logic (FL) are applied to estimate suspended sediment load of the Skunk River in USA. A comparison was performed between fuzzy logic (FL) and sediment rating-curve (SRC). It was based on a 5 years period of continuous streamflow, suspended sediment concentration data of Skunk Augusto Station operated by the United States Geological Survey. Based on comparison of the results, it is found that the FL model gives better estimates than the other technique.
Keywords: suspended sediment; forecasting; fuzzy logic; sediment rating curve