investigation of the efficiency of the fuzzy regression method in reconstructing monthly discharge data of hydrometric stations in great karoon river basin

there are different methods of reconstructing hydrologic data. depending on the conditions of the station a particular method can produce the best results. generally, in order to estimate the lost data in a station and its surrounding stations, hydrologic, climatologic and/or physiolographic similarities are used. recently, the fuzzy regression method has been used to reconstract the hydrologic data. in this research, the efficiency of this method in reconstructing the montly discharge data of hydrometric stations in comparison to other methods was investigated. the credited omission method was used in this investigation, then by omitting the observed data deliberately, their values were estimated using the different methods. afterwards, by the use of the statistical index of root mean squared error (rmse) the best method of reconstruction was determined. the results showed that the best methods of reconstructing monthly discharge data for the hydrometric stations in the great karoon river basin in order of accuracy are artificial neural network, simple linear regression, multiple linear regression, normal ratio, fuzzy regression, autoregresive and graphical methods.