Soil and water salinities are major environmental factors limiting the productivity of agricultural lands especially in arid and semi-arid regions. This study was carried out in two different soil textures to simulate the relationship among yield, irrigation water salinity and soil salinity for different crops such as cotton, maize, alfalfa, barley and wheat for an arid region located in Semnan Province, central part of Iran with area of 35000 ha including 94 villages belonged to irrigation network of Garmsar District (52 ? 25' N 35 ? 11' E). For simulation, the SWAP model was linked to the SENSAN model. The data collected from the above 94 villages for years 1998 to 2007 were used to calibrate and evaluate yield of above crops using the SWAP model. The model was calibrated for above crops based on potential yields and then verified based on ten years yield data. Results of the model analysis showed that SWAP model is able to predict yield with good degree of accuracy. The simulated yields of cotton, maize, alfalfa, barley and wheat corresponded well with the observed yield values. The sensitivity of the crops to soil and irrigation water salinities were determined and more salt tolerance crops were selected for the study area. Wheat was found to be more sensitive to salinity as compared with cotton, but it was more salt tolerance than maize and alfalfa. Then the percentages of groundwater combination with surface water for irrigation by using combining SWAP model and genetic algorithm were determined. The percentage of groundwater means percentage of original groundwater that farmers in the study area are using and combining with surface water minimum objective function accrued when 80% of groundwater is combined with surface water for irrigation. Keywords : Simulation, optimization, salinity, salt tolerance, combining saline water with irrigation water, yield reduction
