Development of the framework of an irrigation management optimization model considering crop rotation
In arid and semi-arid countries such as Iran, the uneven spatial and temporal distribution of rainfall necessitates a reliance on irrigated agriculture for food production. Consequently, a substantial portion of water resources is allocated to agriculture. Identifying strategies reducing water consumption and improving its efficiency in agriculture are critical priorities. This study employs crop rotation as a key variable in an optimization framework to calculate a matrix of impact coefficients based on insights from expert farmers. The matrix quantifies the effects of sequential crop planting. These coefficients are incorporated into a water allocation optimization model aimed at maximizing economic profitability, utilizing a genetic algorithm and the AquaCrop plug-in program. For this purpose, C# coding within Visual Studio was used to optimize three-, four-, five-, six-, and seven-year rotations involving wheat, soybean, tomato, potato, corn, alfalfa, barley, and sugar beet. Moreover, the impact of crop rotation on crop yield, water allocation, and expected profitability per unit area was evaluated using a valuation formula. Rotation Optimization results indicated that the four-year rotation (sugar beet, corn, potato, tomato) achieved the highest economic profit, while the seven-year rotation was most effective in reducing water allocation (by 9.45%). Therefore, crop rotation optimization is a significant parameter for enhancing crop yield, boosting profitability, and achieving long-term water savings.
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Scheduling and optimal delivery of water in irrigation networks by combining the AquaCrop model and genetic algorithm
Parisa Kahkhamoghadam, Ali Naghi Ziaei *, , Amin Kanooni, Sedigheh Sadeghi
Journal of Water and Soil Management and Modeling, -
Assessment of suitable areas for cultivation of wheat, corn, sugar beet, and tomato in different climates of Iran considering the climate change effects using AquaCrop model
Maedeh Soltani Sistani, Hossien Ansari *, , Mohammadreza Naghedifar
Iranian Journal of Soil and Water Research,