The Weather Generation Model “LARSWG” and hydrological Model “SWAT” used in this study to estimate the quantity of future surface runoff in the Sahiliya Valley located within the Iraqi western desert. The weather data for the last ten years used as input in the LARSWG model to generate future weather data under the effect of climate change. In this model, the statistical test analysis done automatically, with two statistical test values, the (KS-value) test and the (p-value) test. The results of these tests are equal or close to zero (0.0) for KS-values, and equal or somewhat close to one (1.o) for p-values, which means the LARS-WG model is perfect for generating rainfall and temperature, and is more suitable in simulating the seasonal distributions. Data results from the LARSWG model used as input weather data in the SWAT model. For the SWAT model, several data are required for its software operation such as a digital elevation model, Land use-land cover, soil map, and weather data. SWAT modeling was done for watershed delineation for this valley yielding (14) sub-basins and (59) hydrological response units. To test the suitability of applying this model, two Statistical tests (Nash-Sutcliffe - NS) and Coefficient of determination - R2 test were applied for the two sets of data on Surface Runoff in both calibration and validation periods.  The results of these tests are (0.72) (0.78) for calibration, and (0.64) (0.67) for validation respectively. The values of the (NS) test for both simulated and calculated data in the calibration and validation periods are somewhat similar. Also, the same goodness of results in the (R²). The data results from SWAT modelling shows that maximum runoff occurs in October and November in winter season, and March in spring season in each year, and the runoff occurs at a rate of one to four (1-4) times annually, and in some years twice only. This means that the amount of surface runoff water added to the Euphrates River is limited from this valley.