Optimization method for crop irrigation scheduling based on simulation technique and genetic algorithms

Based on soil water balance model, soil water content and field evapotranspiration during crop growth stage were simulated dynamically. The crop yield was obtained through Jensen model of crop water-production function. An optimization model for crop irrigation scheduling was established with the irrigation date as the decision variable and the maximal relative yield as the decision objective, and was optimized using elitist-reserved genetic algorithm (GA). The model was used to optimize the irrigation scheduling for winter wheat after greening with the 2003 meteorology data in Xiaohe irrigation area, Shanxi Province. Optimized results with dynamic programming, simplex evolutionary algorithm and GA were analyzed. Result shows that GA is effective in global optimization and results with GA are stable. Irrigation in the early heading stage is the most efficient with irrigation in the shooting stage being the second. Field evapotranspiration and crop yield increase with the irrigation volume, but with decreasing slopes.