Abstract Meteorology and hydrology are based on data mining and data analysis. The basis of hydrological and meteorological studies is the acceptable statistical data. In order to take action and engineering the data, the efficiency and reliability of the data must be ensured before starting the work. To obtain reliable data, hydrological models are used, which have undergone many changes over the past years. Therefore, in this study, in order to eva‎luate the accuracy of precipitation data in Isfahan province using the CMIP5 models during the base period (1995-2010) as well as the projected data for the future (2010-2030). For this purpose, precipitation data from two models (CanESM2 and GISS-E2-R) were analyzed using statistics such as R2, RMSE, and BIAS. Also, using the Kendall Man test, the future precipitation trend of the province was examined. The results showed that neither of the two models had the sufficient accuracy and ability to estimate precipitation in the province and according to the research statistics are in the range of moderate to poor accuracy. However, the CanESM2 model showed relatively better results. Although it did not have an accurate accuracy in estimating precipitation, it had a relatively good ability to estimate precipitation time cycles. Further review of the validation results of the selected model showed that the results are consistent with the results of the eva‎luation phase. The results of the climatic scenarios 4/5 and 8/5 of the selected models were almost the same, although scenario 4/5 recorded relatively better performance. From the trends of two scenarios, 4/5 and 8/5 precipitation, the CanESM2 model showed that the trend of precipitation changes will not be significant for any of the regions. Then, using GAMS and coding with the application of target functions, the best points for the construction of the station under two scenarios were investigated. The first scenario was assumed that there were no stations in the study area and the number of available stations was estimated based on the size of the area, in which according to the calculations and after using the existing objective function, 20 stations were placed in the area. In the second scenario, the average rainfall of stations in the region was used to estimate the number of necessary stations in the region, which finally added three stations to the region by examining the defined objective function.

سعيد اسلاميان

جهانگير عابدي كوپايي ، سعيد سلطاني كوپايي