عنوان مقاله [English]
A deficit in precipitation (meteorological drought) can result in a recharge deficit, which in turn causes lowered surface flow and a deficit in groundwater discharge. Given the importance of water in human life, regulating the access to reliable and sustainable water resources and planning proper consumption are essential for every designated region. There are two type of limitations that results from natural phenomena or improper management by human. This phenomenon is evident when above mentioned two factors emerge together. The purpose of this study is to identifying the climatic conditions that affect the flow in Dehgolan basin. The applied dataset in this study is the Precipitation, temperature, evaporation and runoff recorded in stations located at the Dehgolan basin. First using the Double-Mass curve the accuracy and the exactness of the mentioned data checked. Having made sure of their accuracy, using the data of adjacent stations and through proportions and differentials, the lost data of each station rebuilt. Drought occurrence was calculated using SPI index and other climatic variables normalized too. Then operative climatic conditions on surface flow studied using the artificial neural network in MATLAB environment as the method of feed forward back propagation. The highest correlation coefficient and proper mean square error for the input parameters obtained in an input model include: SPI in half year time scale, flow in the last months, temperature and evaporation in the synchronic month. Compare the multiple regression method and artificial neural networks shows higher correlation coefficient in artificial neural network. According to the major changes in the values of correlation, Standard Precipitation Index (SPI) and the discharge of the previous month can mention that the variation of these parameters got a higher effect on decreasing or the increasing of the monthly discharge.