Prediction of Soil Profile Water Content and Salinity in Sesame and Maize Fields by SWAP Model under Farmers Management Conditions (Case Study Larestan Region)

In this research the performance evaluation of SWAP model was investigated for simulating of soil water content and salinity under farmers management in an arid region located in Larestan region in Fars province. For this reason، all field experimental data such as soil water content، soil salinity، crop and soil parameters، meteorological parameters and quality and quantity of irrigation water were measured from Sesame and Maize pilot fields، for 2012-2013 periods and model was sensitivity analyzed، calibrated and validated. Performance evaluation based on statistic indices indicated that the model has a high accuracy in simulating of soil water content and salinity. The estimation average of root mean squares errors of soil water content and salinity were calculated for Maize، 0. 019 (cm3cm-3) and 0. 29 dS/m، respectively and for Sesame 0. 01 (cm3cm-3) and 0. 63 dS/m، respectively. The average of NSE for soil salinity obtained for Maize and Sesame 0. 89 and 0. 90، respectively. The NSE calculated for prediction of soil water content to Maize and Sesame، 0. 77 and 0. 79، respectively. So as for predicting of soil salinity and soil water content، with saline irrigation water، SWAP is a precision and appropriate model.