Development of the framework of an irrigation management optimization model considering crop rotation

Document Type : Research Paper

Authors

1 department of science and Water engineering , Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

2 Department of Applied Mathematics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iran

Abstract

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.

Keywords

Main Subjects

EXTENDED ABSTRACT

 

Introduction

A big challenge on a national and global scale is the increasing demand for food due to the growing population and the decrease in the crop yields, so the production in the agricultural sector is very important to solve the crisis. Crop rotation, a sustainable agricultural technique, has been at humanity’s disposal since time immemorial and is practiced globally. Switching between cover crops and cash crops helps avoid the adverse effects of intensive farming. Determining the optimum cash-cover rotation schedule for maximizing yield has been tackled on multiple fronts by agricultural scientists, economists, biologists and computer scientists, to name a few. However, considering the uncertainty due to diseases, pests, droughts, floods and impending effects of climate change is essential when designing rotation strategies. Crop models are considered as an important tool for design and evaluation in order to adequately describe product development and production, but the main forms should not be too complex, or have long calculations. The AquaCrop provided by FAO is highly accurate and not complicated. Furthermore, this model has been developed for more than 15 products in different locations. Aqua Crop is an effective tool that can calculate and predict the total biomass and final yield for different irrigation strategies including no water stress to low stress or in some cases severe water stress with acceptable accuracy.  Optimizing water usage leads to preserving water resources and improving the quality of crops. Optimization is used to control and manage the water usage in agriculture and reduce the amount of water used in plants, it should be noted that this method takes into account the highest economic profit.

Materials and Methods

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 entries of this matrix quantify the impact coefficients of sequential crop planting. The impact coefficient of crop rotation is integrated into a water allocation optimization model designed to maximize economic profitability, utilizing a genetic algorithm and the AquaCrop plug-in program. For this purpose, C# coding within the framework of Visual Studio was carried out to optimize three-, four-, five-, six-, and seven-year rotations with wheat, soybean, tomato, potato, corn, alfalfa, barley, and sugar beet. Moreover, the impact of crop rotation on crop yield and water allocation as well as the expected profitability per unit area was assessed using a valuation formula.

Results and Discussion

An optimization model for the allocation of water resources with the aim of maximizing economic profit based on genetic algorithm was used to generate irrigation and crop rotation data to determine the combination of crop cultivation with maximum economic profit, so that the limitation related to water availability is established. The generated irrigation data was used as an input to AquaCrop, and the output of crop yield was obtained from the software. C# (C-Sharp) coding was used in the Visual Studio environment to optimize this cycle. The optimization model used in this study is able to implement 20% less irrigation. The study of the effect of low irrigation on crop yield showed that the implementation of crop rotation reduces the effects of low irrigation on the yield score of the crop, so that the lowest reduction of the optimum yield score of the crop compared to the deficit irrigation yield of wheat and alfalfa crops was obtained 7 and 7.8, respectively. Also, the highest decrease in the optimum yield score compared to the yield of 20% deficit irrigation of the corn crop was observed by 23% in the 4-yr period and 22.8% in the 7-yr period.

Conclusion

In this study, crop rotation was used as an effective factor in the optimization equation to calculate the matrix of the impact factor of crop rotation, using the opinion of expert farmers, in order to reduce consumption and optimal use of water resources. The optimization method described in this research was used to calculate the optimal cultivation pattern and irrigation planning for eight crops of wheat, barley, potato, sugar beet and alfalfa as winter crops, corn, tomato and soybean as summer crops under the weather conditions of Mashhad. The genetic algorithm has been used for this economic decision-making model that considers the impact of the agricultural cycle on the economic yield during several growing seasons. According to the results of this study, for the studied area, the highest frequency of wheat and potato crop is in different intervals and the lowest frequency is soybean crop. Also, the best rotation was obtained in terms of 4-yr rotation profit score (sugar beet, corn, potato and tomato). It is suggested that future researches focus on improving the optimization speed, accuracy and formulation of an advanced objective function for crop models.

 

Author Contributions

Conceptualization: Kamran Davary; Methodology: Seyed Mohammadreza Naghedifar; Software: Seyed Mohammadreza Naghedifar, Sedigheh Sadeghi, and Mohammad Ali Boush; Validation: Kamran Davary, Seyed Mohammadreza Naqedifar, and Hossein Banejad; Formal analysis: Kamran Davary and Mohammad Ali Boush; Investigation: Seyed Mohammadreza Naqedifar, Hossein Banejad, and Mohammad Ali Boush; Resources: Mohammad Ali Boush; Data curation: Kamran Davary and Seyed Mohammadreza Naqedifar; Writing—original draft preparation: Mohammad Ali Boush; Writing—review and editing: Mohammad Ali Boush; Visualization: Hossein Banejad; Supervision: Kamran Davary and Hossein Banejad; Project administration: Kamran Davary; Funding acquisition: Kamran Davary.

All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The data were extracted from a thesis with the project number (57828) and title: "Optimization of Irrigation Management with Emphasis on Crop Rotation and Price Risk."

Acknowledgements

The authors would like to extend their heartfelt thanks to Ferdowsi University of Mashhad for providing the necessary support and resources for this research. The university's commitment to academic excellence has been instrumental in facilitating this project.

Additionally, the authors wish to express their sincere gratitude to the esteemed faculty members of Ferdowsi University, including Dr. Kamran Davary, Dr Seyed Mohammadreza Naghedifar, Dr Hossein Banejad, and Sedigheh Sadeghi. Their invaluable contributions, expert insights, and continuous support were essential to the successful completion of this research. The authors deeply appreciate their dedication and collaboration throughout the process.

Ethical considerations

The authors avoided data fabrication, falsification, plagiarism, and misconduct.

Conflict of interest

The author declares no conflict of interest.

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Iranian Journal of Soil and Water Research
Volume 55, Issue 12
March 2025
Pages 2391-2408

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