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

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Abstract

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.

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Authors and Affiliations

  1. Department of Water Engineering, University of Zabol, Zabol, Iran

    Omolbani Mohammadrezapour & Icen Yoosefdoost

  2. Department of Agricultural, Payame Noor University (PNU), Tehran, Iran

    Mahboube Ebrahimi

Authors
  1. Omolbani Mohammadrezapour
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  2. Icen Yoosefdoost
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  3. Mahboube Ebrahimi
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Correspondence to Omolbani Mohammadrezapour.

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The authors whose names are listed in this manuscript certify that they have NO affiliations with or involvement in any organization or entity with any financial interest or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.

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Mohammadrezapour, O., Yoosefdoost, I. & Ebrahimi, M. Cuckoo optimization algorithm in optimal water allocation and crop planning under various weather conditions (case study: Qazvin plain, Iran). Neural Comput & Applic 31, 1879–1892 (2019). https://doi.org/10.1007/s00521-017-3160-z

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