JWSS - Journal of Water and Soil Science

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Since the fluctuations of the Persian Gulf Sea Surface Temperature (PGSST) have a significant effect on the winter precipitation and water resources and agricultural productions of the south western parts of Iran, the possibility of the Winter SST prediction was evaluated by multiple regression model. The time series of PGSSTs for all seasons, during 1947-1992, were considered as predictors, and the time series of MSSTs during 1948-1993, as the prrdictand. For the purpose of data reduction and principal components extraction, the principal components analysis was applied. Just the scores of the first four PCs (PC1 to PC4) that accounted for the total variance in predictor field were considered as the input file for the regression analysis. For finding the dependency of each principal component to the first time series of the PGSST, the Varimax rotation analysis was applied. The results have indicated that PC1 to PC4 respectively are the indicator of temperature changes during winter, autumn, Spring and Summer. According to the regression model, the components of PC1, PC2 and PC4 were significant at 5% level. But the components of PC3 was insignificant. The results indicated that the significant variables are held accountable for the 33.5% of the total variance in the winter PGSSTs. It became obvious that for the prediction of the winter PGSST, the PGSST during the winter of the last year has a particular importance. At the next stage, autumn and summer temperature have also a role in prediction of winter PGSST.

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In the last decades, climate change and fluctuation of water balance have been the main reason to apply hydrologic models for estimating quality and quantity of water components as efficient tools in water planning of critical conditions. In addition, these hydrologic models with potential to study the effects of watershed management practices on the runoff components are suitable tools for optimization of watershed operations at present and future. In this research Soil and Water Assessment Tools (SWAT) model has been applied to estimate groundwater runoff  for 6 provinces such as Eilam (Golgol Catchment), Boushehr (Baghan Catchment), Khozestan (Morghab Catchment), Fars (Shekastian Catchment), Kohkiloyeh & Boyer Ahmad(Tange Birim Catchment) and Hormozgan (Daragah Catchment) which are located in south and south west of Iran. In order to evaluate the performance of the model, hydrological data, soil, land use and Digital Elevation Model (DEM) entered for each catchment to run the SWAT model. SWAT-CUP with SUFI2 program was used for simulation, uncertainty and validation with 95ppu. P-factor and R-factor are two internal evaluation factors in SUFI2 program and indicators such as the coefficient of determination (R²) and Nash- Sutcliffe (NS) were used for evaluation of the model. The Nash-Sutcliffe coefficients in six mentioned catchments for calibration period are 0.66, 0.73, 0.40, 0.32, 0.53 and 0.78. They are 0.49, 0.48, 0.42, 0.45, 0.46 and 0.62 for validation period, respectively. Model calibration and validation results showed good performance in estimating the water balance of the basins studied. Except for Shecastian catchment, the evaluation results showed acceptable and favorable results for water balance in the study area.