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Irrigation Systems Transformation in Cotton Production in the Harran District, Turkey: Implications of an Agent-Based Model

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Listed:
  • Onur YENİ
  • Zeynep YENER-GÖK
  • Özgür TEOMAN

Abstract

Agricultural water use for irrigation in Turkey is higher than OECD averages. The main reason for this is the widespread use of surface irrigation methods. Since Turkey is not a water-rich country, high agricultural water use can be considered as a serious sustainability problem. Cotton, as an industrial crop, keeps its importance in Turkey in terms of its added value and foreign exchange inflow it provides directly and indirectly. This study scrutinizes the transformation of existing irrigation systems in Harran district by employing an agent-based model and also calculates the amount of areabased irrigation support required to ensure this transformation.

Suggested Citation

  • Onur YENİ & Zeynep YENER-GÖK & Özgür TEOMAN, 2020. "Irrigation Systems Transformation in Cotton Production in the Harran District, Turkey: Implications of an Agent-Based Model," Sosyoekonomi Journal, Sosyoekonomi Society, issue 28(45).
    • Handle: RePEc:sos:sosjrn:200315
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    References listed on IDEAS

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    1. Ebru Solakoglu & Sabri Er & M. Solakoglu, 2013. "Technical Efficiency in Cotton Production: The Role of Premium Payments in Turkey," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 20(3), pages 285-294, November.
    2. Ghazali, Mahboubeh & Honar, Tooraj & Nikoo, Mohammad Reza, 2018. "A hybrid TOPSIS-agent-based framework for reducing the water demand requested by stakeholders with considering the agents’ characteristics and optimization of cropping pattern," Agricultural Water Management, Elsevier, vol. 199(C), pages 71-85.
    3. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    4. Turrell, Arthur, 2016. "Agent-based models: understanding the economy from the bottom up," Bank of England Quarterly Bulletin, Bank of England, vol. 56(4), pages 173-188.
    5. Oudendag, Diti & Hoogendoorn, Mark & Jongeneel, Roel, 2014. "Agent-Based Modeling of Farming Behavior: A Dutch Case Study on Milk Quota Abolishment and Sustainable Dairying," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182700, European Association of Agricultural Economists.
    6. Farhadi, Saber & Nikoo, Mohammad Reza & Rakhshandehroo, Gholam Reza & Akhbari, Masih & Alizadeh, Mohammad Reza, 2016. "An agent-based-nash modeling framework for sustainable groundwater management: A case study," Agricultural Water Management, Elsevier, vol. 177(C), pages 348-358.
    7. Thomas Berger & Christian Troost, 2014. "Agent-based Modelling of Climate Adaptation and Mitigation Options in Agriculture," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 323-348, June.
    8. Jagpreet Chhatwal & Tianhua He, 2015. "Economic Evaluations with Agent-Based Modelling: An Introduction," PharmacoEconomics, Springer, vol. 33(5), pages 423-433, May.
    9. Happe, Kathrin & Kellermann, Konrad & Balmann, Alfons, 2006. "Agent-based analysis of agricultural policies: An illustration of the agricultural policy simulator AgriPoliS, its adaptation and behavior," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11(1).
    10. Arthur, W. Brian, 2006. "Out-of-Equilibrium Economics and Agent-Based Modeling," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 32, pages 1551-1564, Elsevier.
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    More about this item

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water

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