Patterning Different Crops Yield with Saline Water Irrigation Condition Using SWAP Model

In this study, the effects of different quality and quantity levels of irrigation water on crop yield, soil water and solute transport were simulated using SWAP model. Field experiments were conducted for the six main crops of the region such as wheat, barley, onion, sunflower and sugar beet at Rudasht drainage and soil reclamation research station. The effects of water salinity under different irrigation managements on crop yield, crop yield components and soil salinity were investigated. The SWAP model was calibrated by inverse modeling and was linked with the PEST model. The model calibration consisted of hydraulic parameters of soil layers as well as solute transport and crop parameters. In order to evaluate modeling validity, statistical indices such as coefficient of determination, root mean square error, modeling efficiency and coefficient of residual mass were calculated. Result of the model analysis showed that with precise calibration, SWAP model is able to predict soil water and solute transport and crop yield with high degree of accuracy. To determine crop-water-salinity production functions, SWAP model was linked to the SENSAN model, then by changing irrigation water depth and salinity values, the model was executed. In order to determine optimal production function for each crop, six functions including linear, cobb douglas, transcendental, translog, quadratic and the Leontief were examined and the pertinent parameters were determined with ordinary least square method using SHAZAM model. Based on statistical indices the optimal production function for wheat, barely, sugar beet, onion and cotton were adjusted Leontief and for sunflower was quadratic.