Optimal allocation of water and land in Moghan irrigation network using crop model and genetic algorithm

Water is one of the most important physical factors to provide the food security of the world’s growing population. The limitation of Iran’s water resources, as well as the increasing competition of different sectors for the use of water make the optimal management of water resources necessary. Different strategies are used in irrigation networks for water resources management. One of these strategies is optimal allocation of water and land. In this research, an optimization model for water and land allocation with the aim of maximizing economic benefit is presented based on genetic algorithm and using the AquaCrop plug-in model. For this purpose, #C coding was done in Visual Studio. In order to measure the model performance, the lands covered by one of the Moghan irrigation network channels were investigated. In this model, the agricultural year was divided into 36 periods of ten days. The irrigation water depth in each period and the cultivated area were considered as decision variables. The results show that the highest increase in percentage of economic benefit is related to the first-cultivation maize, alfalfa and wheat by 9, 7.3 and 7 percent respectively. Although the lowest increase in economic benefit is related to the second-cultivation seed maize and soybeans. The optimal allocated water volume was decreased by 14.7 percent, meanwhile the economic benefit was increased by 5.7 percent. Therefore, the optimal water allocation in this region encourages saving water consumption more than increasing economic benefit.