The study of meteorological characteristics and its variability is important in assessing the climate change impacts for water resources management. Trend analysis of hydrological and meteorological time series is a method for determining the change in climate variables that is performed with different parametric and non-parametric methods. In this research, the annual, seasonal and monthly trends were analyzed regarding rainfall and temperature time series for 1986-2017 in 28 stations of Kashafroud basin in the Northeast of Iran. For this purpose, the annual, seasonal and monthly trends were evaluated using non-parametric Mann Kendall and Pettitt test at 95% level significance. The results showed the trend for the monthly maximum temperature in spring and winter and also the annual trend for all stations was increasing, whereas the summer and autumn pattern differed. The trend of minimum temperature in all seasons and stations do not have a uniform pattern. The results of precipitation trend indicated that the annual precipitation of the basin had not changed and did not have a significant trend in 5% level of significance. Precipitation of the basin in the winter decreased. There was an increasing trend in the Southern half of the basin in autumn. The noticeable decrease of precipitation in winter season especially during January and February with an increase in November can be a serious challenge for water resource management of basin during the dry season.

 Assessing and predicting future climate change is of particular importance due to its adverse effects on water resources and the natural environment, as well as its environmental, economic and social effects. Meanwhile, rainfall is also an important climatic element that causes a lot of damage in excess conditions. West Azerbaijan Province is no exception. The aim of this study is to model and predict 30 years of rainfall in West Azerbaijan province. The statistical period studied is 32 years (2019-1987). Selected stations in the province include Urmia, Piranshahr, Takab, Khoy, Sardasht, Mahabad and Mako stations. Average slider time series models, Sarima (seasonal Arima), Health Winters were used for analysis and prediction and also linear regression and Mann-Kendall test were used to determine the data trend. The results show an increasing trend of precipitation in Urmia, Piranshahr, Khoy, Sardasht and Mako stations and a decreasing trend in Takab and Mahabad stations. According to the results of comparing the models used, the Health Winters model with the least error in the absolute mean of deviations, mean squared deviations and the percentage of absolute mean errors was introduced as the best precipitation forecasting model for West Azerbaijan province. province.                                     [A1] 

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