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A Survey on the Performance of Fuzzy-Neural Network at Predicting the Average Monthly Discharge of Catchment Basin Areas Having Snow Regimes Original Article, D72 Abbasi D., Ashrafzadeh A., Asheghi R., Merufinia E. J. Civil Eng. Urban. 4(4): 480-484. 2014 ABSTRACT: Snow is one kind of precipitation that because of its delay in turning into runoff water is much more different from other kinds of precipitation when it comes to modeling how to turn into water. Statistical models and regression are some of the most common analytical methods which mostly, due to solving this phenomenon linearly, are presenting results with errors and are incapable of modeling over-the-time changes of the considered phenomenon with acceptable accuracy. Nowadays intellectual fuzzy and neural systems, considering their abilities at solving nonlinear and complex phenomena, have a wide use in various engineering problems especially in Hydrology. In this study, by using the abilities of fuzzy-neural networks, is tried to create a model which has the least amount of information to perform for predicting the average monthly discharge in Jajrud River. Since Jajrud River is located in a basin with a mostly snowy regime, it’s meant to find a deducible relation between the average monthly discharge and information of the water equivalent of basin’s snow monitoring stations. Keywords: Average monthly discharge, Neural fuzzy network, Snow melting modeling, Jajrud catchment basin منبع: [Hidden Content] دانلود: [Hidden Content].,%204%20(4)%20480-484,%202014.pdf J. Civil Eng. Urban., 4 (4) 480-484, 2014.pdf