Application of swap model to predict yield and soil salinity for sustainable agriculture in an arid region

Abstract

Due to lack of suitable water resources, many farmers in Iran are using saline river or groundwater for irrigation, which causes gradual accumulation of salts in the soil. For sustainable agricultural productions, appropriate irrigation management practices should be applied if the saline irrigation water is to be used for irrigation. The soil–water–atmosphere–plant model is a physical-based model that can be used to simulate crop yield and soil salinity, among others. To collect fi eld data to apply to this model as input and calibrate it, a fi eld experiment planted with wheat was conducted on a silty clay loam soil, in central part of Iran (Rudasht region near Isfahan with annual average precipitation of about 80 mm), with three irrigation water salinity levels of 2, 8 and 12 dS/m with/without leaching levels of 4, 19 and 32% with two different irrigation water managements, using factorial design with four replications. The results showed that the model is applicable in this arid region and have low sensitivity to input data of root distribution depth and irrigation water salinity and medium sensitivity to climate data, soil surface layer hydraulic characteristics, leaf area index and amount of irrigation. The model simulated wheat yield and soil salinity and the calibration coeffi cients were obtained. The results showed that the model could be used to predict yield and soil salinity for sustainable agricultural production in an arid region.