B. Motamedvaziri; H. Ahmadi; M. Mahdavi; F. Sharifi; N. Javaheri
Volume 62, Issue 2 , October 2009, , Pages 283-298
Abstract
Estimation of river sediment load is one of the most important issues in design of hydraulic structures, investigating water quality, conserving fish habitat, estimating erosion and determining watershed management effects. There are two methods for estimating sediment load: empirical and hydrological ...
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Estimation of river sediment load is one of the most important issues in design of hydraulic structures, investigating water quality, conserving fish habitat, estimating erosion and determining watershed management effects. There are two methods for estimating sediment load: empirical and hydrological methods. Existence of numerous empirical methods for estimation of river sediment load and a wide range of calibration coefficients shows that a suitable analytical or empirical method does not yet exist to accurately estimate the sediment load. Also, hydrological methods are not able to recognize and separate the specific data measuring conditions and they can not show the temporal variation of sediment loads. In spite of these problems, nowadays, researchers are using Artificial Intelligence methods such as Fuzzy Logic. In this study, the measured suspended sediment load at hydrometric station of Sarcham located on Zanjanroud river is analyzed using USBR and FAO methods (common hydrological methods). Furthermore, suspended sediment load are estimated with a model developed based on Fuzzy Logic rules. In order to estimate suspended load using fuzzy method, one method named Supervised Fuzzy C- mean Clustering Method, is used. Then the results of hydrological and fuzzy methods are compared. The results showed that the temporal variation of sediment loads can be analyzed using a fuzzy method. Also the results obtained using the fuzzy method in comparison with the corresponding values obtained using the usual hydrological methods shows a better correlation with the observed values.
