Cuckoo optimization algorithm in optimal water allocation and crop planning under various weather conditions (case study: Qazvin plain, Iran)

As inferred from its biological nature, agriculture is a key consumer of water resources in many countries. Hence, today, water management plays an important role in the use of water resources of these countries. The present study aimed to optimize cultivation area, to manage irrigation water, and to optimize total income gained from the cultivation area of special crops in Qazvin plain (the central plateau of Iran) under various weather conditions using cuckoo optimization algorithm (COA). Under the same objective function, the performance of the COA was accessed through comparison with the genetic algorithm (GA). The results of two models showed that because of its high water requirement and low yield, the cultivation area of sugar beet in every four different condition reduced (by over 80%); that is, it is not wise to plant it in all different weather conditions of the study area. Comparison of the model results indicates that the COA can provide better and more reliable optimal results in relative yield of crops, higher farm income. So, in comparison with GA, less water is allocated. Following the new cropping pattern delivered by COA model, the water volume stored in the dam reservoir at the end of the operation under wet, normal, dry, and hot–dry conditions rose, respectively, by 264,745.3, 2,865,387, 275,789, and 655,918 m³. Meanwhile, the farmers’ profit increased, respectively, by 6.2, 2.6, 1.27, and 1.48% compared to the previous optimization occurred at the end of the operation. To conclude, COA is quite promising in a cultivation area of crops optimization problem in terms of its simple structure, excellent search efficiency, and strong robustness.