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Optimal Cultivation Pattern to Increase Revenue and Reduce Water Use: Application of Linear Programming to Arjan Plain in Fars Province

Author

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  • Amin Daghighi

    (Department of Civil and Environmental Engineering, Cleveland State University, Cleveland, OH 44115, USA
    Daneshkar Ahwaz Company, Tehran 1987984354, Iran)

  • Ali Nahvi

    (Department of Civil, Construction and Environmental Engineering, Iowa State University, Ames, IA 50011, USA)

  • Ungtae Kim

    (Department of Civil and Environmental Engineering, Cleveland State University, Cleveland, OH 44115, USA)

Abstract

Because the available water resources of the Arjan plain region in Iran do not fully meet the watering requirements for plants in farmlands, the crops suffer from water stress, a situation that causes them to wilt. The aim of this study is to develop a water resources planning model that helps decision-makers determine an appropriate cultivation pattern, optimize the exploitation from surface water resources, and specify the method of allocating water across different farm crops to minimize the detrimental effects of water shortage. Through investigating various models of water resources planning and properties along with the governing conditions for each of these models, the linear programming model was selected as a suitable option due to its simplicity and practical applicability to water resource allocation planning. The model was run for a five-year period by considering gradual variations through the determination of the most appropriate exploitation pattern from the available water resources (surface and groundwater). Results reveal that the negative water balance can be improved gradually as positive, where it will reach +20 million m 3 per year in 2040 from the current deficit of 236 million m 3 with an 8% increased net profit.

Suggested Citation

  • Amin Daghighi & Ali Nahvi & Ungtae Kim, 2017. "Optimal Cultivation Pattern to Increase Revenue and Reduce Water Use: Application of Linear Programming to Arjan Plain in Fars Province," Agriculture, MDPI, vol. 7(9), pages 1-11, September.
    • Handle: RePEc:gam:jagris:v:7:y:2017:i:9:p:73-:d:110882
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    References listed on IDEAS

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    1. Zeng, Xieting & Kang, Shaozhong & Li, Fusheng & Zhang, Lu & Guo, Ping, 2010. "Fuzzy multi-objective linear programming applying to crop area planning," Agricultural Water Management, Elsevier, vol. 98(1), pages 134-142, December.
    2. M. Habibi Davijani & M. E. Banihabib & A. Nadjafzadeh Anvar & S. R. Hashemi, 2016. "Multi-Objective Optimization Model for the Allocation of Water Resources in Arid Regions Based on the Maximization of Socioeconomic Efficiency," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 927-946, February.
    3. Iglesias, Ana & Garrote, Luis, 2015. "Adaptation strategies for agricultural water management under climate change in Europe," Agricultural Water Management, Elsevier, vol. 155(C), pages 113-124.
    4. Shang, Songhao & Mao, Xiaomin, 2006. "Application of a simulation based optimization model for winter wheat irrigation scheduling in North China," Agricultural Water Management, Elsevier, vol. 85(3), pages 314-322, October.
    5. Li, Mo & Guo, Ping, 2015. "A coupled random fuzzy two-stage programming model for crop area optimization—A case study of the middle Heihe River basin, China," Agricultural Water Management, Elsevier, vol. 155(C), pages 53-66.
    6. Dai, Z.Y. & Li, Y.P., 2013. "A multistage irrigation water allocation model for agricultural land-use planning under uncertainty," Agricultural Water Management, Elsevier, vol. 129(C), pages 69-79.
    7. M J López-Baldovin & C Gutiérrez-Martin & J Berbel, 2006. "Multicriteria and multiperiod programming for scenario analysis in Guadalquivir river irrigated farming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 499-509, May.
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    Cited by:

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    2. Ajay Singh, 2022. "Better Water and Land Allocation for Long-term Agricultural Sustainability," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(10), pages 3505-3522, August.
    3. Noha H. Moghazy & Jagath J. Kaluarachchi, 2020. "Sustainable Agriculture Development in the Western Desert of Egypt: A Case Study on Crop Production, Profit, and Uncertainty in the Siwa Region," Sustainability, MDPI, vol. 12(16), pages 1-23, August.
    4. Noha H. Moghazy & Jagath J. Kaluarachchi, 2021. "Impact of Climate Change on Agricultural Development in a Closed Groundwater-Driven Basin: A Case Study of the Siwa Region, Western Desert of Egypt," Sustainability, MDPI, vol. 13(3), pages 1-21, February.
    5. Ijaz Ahmad & Fan Zhang & Junguo Liu & Muhammad Naveed Anjum & Muhammad Zaman & Muhammad Tayyab & Muhammad Waseem & Hafiz Umar Farid, 2018. "A linear bi-level multi-objective program for optimal allocation of water resources," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-25, February.

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