عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Estimation of rivers sediment load is one of the most important problems for design
of hydraulic structures, investigating water quality, conserving fish habitate, estimating
erosion and determining watershed management effects.
There is two metheod for estimating sediment load: empirical and regression
methods. Existence of numerous empirical methods for estimation of river sediment
load, a wide range of calibration coefficients shows that a suitable analytical or
empirical method does not yet exist to accurately estimate the sediment load.
Therefore, the measured discharges and sediment concentrations in hydrometry
stations are statistically analyses for an accurate estimation of sediment loads in rivers.
In usual statistical methods a power function is generally fitted on the data sets of flow
and sediment discharge and thus the total sediment load could be calculated using this
function. These methods are not able to recognize and separate the specific data
measuring conditions. Therefore, they are not only able to accurately estimate the
sediment load, but also can not show the temporal variation of sediment loads. In spite
of this problems, researcher are using Artificial Intelligence methods such as Fuzzy
In this study, the measured suspended sediment load at hydrometry stations of
Telvar River is analyzed using USBR and FAO methods (usual statistical methods).
Furthermore, Sediment suspended load are estimated with a model developed based on
Fuzzy Logic rules. Then the results of these mothods are compared. This research
study has shown 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 statistical methods shows a better
correlation with the observed values. In all stations the fuzzy method estimated the
sediment loads between ones obtained using statistical methods.