<![CDATA[Climate change is one of the most important issues on a global scale, and it has exerted a significant impact on environmental security and livelihoods, both directly and indirectly. In this study, the precipitation trend is assessed by comparing predictand and predictor data from 1990 to 2020. Predictand data were obtained from local organization data sets, and predictor data were taken from the General Circulation Models. Tow models, statistical downscaling model (SDSM), and Long Ashton Research Station Weather Generator (LARS-WG) are applied to downscale and project the future rainfall condition (2025-2100) under RCP2.6, RCP4.5 and RCP8.5. The performance of the two models was checked by using measured indicators (R, R2, MAE, RMSE, and NRMSE). The non-parametric Mann-Kendall test was used to determine the precipitation trend. The results revealed that the precipitation trend is decreasing in the reference period. In the future, it would decrease under RCP2.6 and RCP8.5 except for RCP4.5 by SDSM and RCP4.5 and RCP8.5 except RCP2.6 by LARS-WG. The values of Monthly changes in precipitation (%) under RCP2.6, RCP4.5, and RCP8.5 are 0.3 to 2.7%, 0.4 to 2.7%, and 0.4 to 2.8% in December, August, March, and April, respectively. Seasonal changes in precipitation under RCPs ranged from 4.87 to 4.89% in spring, 0.01% in summer, 2.43 to 1.76% in autumn, and 4.35 to 4.63% in winter. The change in precipitation during the spring season is decreasing, whereas it is increasing in the autumn.]]>
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