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Surface irrigation simulation-optimization model based on meta-heuristic algorithms

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  • Akbari, Mahmood
  • Gheysari, Mahdi
  • Mostafazadeh-Fard, Behrouz
  • Shayannejad, Mohammad

Abstract

Simulation-optimization models are valuable tools for determining the optimal performance of systems. The main objective of this research was to develop and validate EDOSIM (Evaluation, Design, and Optimization of Surface Irrigation Model) as a simulation-optimization model for surface irrigation systems. For simulation, which consisted of the design or evaluation of basin, border and furrow irrigation, the Volume Balance model was used. For optimization, twenty meta-heuristic algorithms were applied. In this model, based on irrigation, the volume of infiltrated water to soil was calculated without having advance and recession data. The hydraulic objective function was used to minimize the linear combination of seven performance indicators. Regarding the optimization of the objective function, the functional, multi-dimensional, static, constraint, continuous, single-objective, and meta-heuristic optimizations were applied. Data obtained from fifteen experimental fields were used for the validation of simulation, algorithms parameters setting, and validation of optimization. Comparison of the simulation results of the EDOSIM model with those of the Hydrodynamic model of SIRMOD software showed the good performance of EDOSIM model and the proposed method for estimating the volume of infiltration with RMSE = 0.068, R2 = 0.988, CRM = 0.005 and NRMSE = 4.2%. The Shuffled Complex Evolution (SCE) algorithm was found to be the best algorithm for the optimization of fields; in all fields, the objective function was decreased (improved). Comparison of the objective function of the EDOSIM model with eight solvers of Optimization and Global Optimization Toolboxes of MATLAB software also revealed the superiority of the EDOSIM model for optimization.

Suggested Citation

  • Akbari, Mahmood & Gheysari, Mahdi & Mostafazadeh-Fard, Behrouz & Shayannejad, Mohammad, 2018. "Surface irrigation simulation-optimization model based on meta-heuristic algorithms," Agricultural Water Management, Elsevier, vol. 201(C), pages 46-57.
    • Handle: RePEc:eee:agiwat:v:201:y:2018:i:c:p:46-57
    DOI: 10.1016/j.agwat.2018.01.015
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    References listed on IDEAS

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    2. Eltarabily, Mohamed Galal & Mohamed, Abdelmoneim Zakaria & Begna, Sultan & Wang, Dong & Putnam, Daniel H. & Scudiero, Elia & Bali, Khaled M., 2024. "Simulated soil water distribution patterns and water use of Alfalfa under different subsurface drip irrigation depths," Agricultural Water Management, Elsevier, vol. 293(C).
    3. Jingjing Wu & Jian Chen & Yu Han & Tongshu Li, 2020. "Study on Unsteady Flow Based on Optimized Water Distribution Model in Irrigation District," Sustainability, MDPI, vol. 12(4), pages 1-13, February.
    4. Zhang, Haowen & Liang, Qing & Peng, Zhengping & Zhao, Yi & Tan, Yuechen & Zhang, Xin & Bol, Roland, 2023. "Response of greenhouse gases emissions and yields to irrigation and straw practices in wheat-maize cropping system," Agricultural Water Management, Elsevier, vol. 282(C).
    5. Nie, Wei-Bo & Dong, Shu-Xin & Li, Yi-Bo & Ma, Xiao-Yi, 2021. "Optimization of the border size on the irrigation district scale – Example of the Hetao irrigation district," Agricultural Water Management, Elsevier, vol. 248(C).
    6. Xin Zhang & Jianheng Zhang & Liwei Li & Yang Liu & Wenchao Zhen & Guiyan Wang, 2024. "Interaction Effects of Water and Nitrogen Practices on Wheat Yield, Water and Nitrogen Productivity under Drip Fertigation in Northern China," Agriculture, MDPI, vol. 14(9), pages 1-19, September.
    7. Liu, Minguo & Wang, Zikui & Mu, Le & Xu, Rui & Yang, Huimin, 2021. "Effect of regulated deficit irrigation on alfalfa performance under two irrigation systems in the inland arid area of midwestern China," Agricultural Water Management, Elsevier, vol. 248(C).
    8. Pazouki, Ehsan, 2021. "A practical surface irrigation system design based on volume balance model and multi-objective evolutionary optimization algorithms," Agricultural Water Management, Elsevier, vol. 248(C).
    9. Pazouki, Ehsan, 2021. "A practical surface irrigation design based on fuzzy logic and meta-heuristic algorithms," Agricultural Water Management, Elsevier, vol. 256(C).
    10. Pazouki, Ehsan, 2023. "A smart surface irrigation design based on the topographical and geometrical shape characteristics of the land," Agricultural Water Management, Elsevier, vol. 275(C).
    11. Costabile, Pierfranco & Costanzo, Carmelina & Gangi, Fabiola & De Gaetani, Carlo Iapige & Rossi, Lorenzo & Gandolfi, Claudio & Masseroni, Daniele, 2023. "High-resolution 2D modelling for simulating and improving the management of border irrigation," Agricultural Water Management, Elsevier, vol. 275(C).
    12. Nie, Wei-Bo & Li, Yi-Bo & Zhang, Fan & Ma, Xiao-Yi, 2019. "Optimal discharge for closed-end border irrigation under soil infiltration variability," Agricultural Water Management, Elsevier, vol. 221(C), pages 58-65.
    13. Carlos Chávez & Sebastián Fuentes & Carlos Fuentes & Fernando Brambila-Paz & Josué Trejo-Alonso, 2022. "How Surface Irrigation Contributes to Climate Change Resilience—A Case Study of Practices in Mexico," Sustainability, MDPI, vol. 14(13), pages 1-13, June.

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