IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v277y2023ics0378377422006825.html
   My bibliography  Save this article

Linking agricultural water-food-environment nexus with crop area planning: A fuzzy credibility-based multi-objective linear fractional programming approach

Author

Listed:
  • Zhang, Chenglong
  • Yang, Gaiqiang
  • Wang, Chaozi
  • Huo, Zailin

Abstract

To readily addressed three key issues including fuzzy parametric information, multiple objectives and fractional ratios in planning problems, this study presents a fuzzy credibility-based multi-objective linear fractional programming approach for building the linkage between agricultural water-food-environment nexus and crop area planning. This approach is developed by incorporating fuzzy credibility-constrained programming into multi-objective linear fractional programming within the optimization model. To demonstrate its applicability, the approach is then applied to the Hetao Irrigation District in the northwest China to unite the multiple objective problems in agricultural irrigation with crop area planning. Three ratio optimization problems associated with agricultural, economic and environmental objectives are concurrently considered including maximum economic benefit per unit of irrigation water, maximum crop yield per unit of irrigated area and minimal grey water footprint per unit of crop production. Therefore, this study has the following advantages. (1) Fuzzy parameters existing in the objective and violated constraints can be effectively tackled. (2) The multiple ratio optimization problems can be efficiently solved through a linearization procedure in a straightforward manner, thereby reflecting desired system efficiency and reducing computational difficulties. (3) The mathematical and practical interactions of agricultural water-food-environment nexus can be investigated based on intermediate variables, i.e., irrigated area, irrigation water, crop yield, economic benefits and greywater footprint. (4) Optimal solutions can be flexibly generated to facilitate crop area planning through given aspiration levels of objective goals and credibility levels of constraints. The results indicate that optimal objective values have slight changes with the form of each objective (e.g., maximization or minimization). The results are useful for facilitating insightful interpretation of inter-relationships among sustainable agricultural production, efficient irrigation water use, and favorable agro-ecological conditions.

Suggested Citation

  • Zhang, Chenglong & Yang, Gaiqiang & Wang, Chaozi & Huo, Zailin, 2023. "Linking agricultural water-food-environment nexus with crop area planning: A fuzzy credibility-based multi-objective linear fractional programming approach," Agricultural Water Management, Elsevier, vol. 277(C).
    • Handle: RePEc:eee:agiwat:v:277:y:2023:i:c:s0378377422006825
    DOI: 10.1016/j.agwat.2022.108135
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377422006825
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2022.108135?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Karrou, M. & Oweis, T., 2012. "Water and land productivities of wheat and food legumes with deficit supplemental irrigation in a Mediterranean environment," Agricultural Water Management, Elsevier, vol. 107(C), pages 94-103.
    2. Gordon, Line J. & Finlayson, C. Max & Falkenmark, Malin, 2010. "Managing water in agriculture for food production and other ecosystem services," Agricultural Water Management, Elsevier, vol. 97(4), pages 512-519, April.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. 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.
    5. Mojtaba Borza & Azmin Sham Rambely, 2021. "A New Method to Solve Multi-Objective Linear Fractional Problems," Fuzzy Information and Engineering, Taylor & Francis Journals, vol. 13(3), pages 323-334, July.
    6. C. Ren & P. Guo & M. Li & J. Gu, 2013. "Optimization of Industrial Structure Considering the Uncertainty of Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(11), pages 3885-3898, September.
    7. Rong, Aiying & Lahdelma, Risto, 2008. "Fuzzy chance constrained linear programming model for optimizing the scrap charge in steel production," European Journal of Operational Research, Elsevier, vol. 186(3), pages 953-964, May.
    8. Jimenez, Mariano & Arenas, Mar & Bilbao, Amelia & Rodri'guez, M. Victoria, 2007. "Linear programming with fuzzy parameters: An interactive method resolution," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1599-1609, March.
    9. Zhang, Chenglong & Guo, Ping, 2018. "FLFP: A fuzzy linear fractional programming approach with double-sided fuzziness for optimal irrigation water allocation," Agricultural Water Management, Elsevier, vol. 199(C), pages 105-119.
    10. Zhang, Chenglong & Li, Xuemin & Guo, Ping & Huo, Zailin, 2021. "Balancing irrigation planning and risk preference for sustainable irrigated agriculture: A fuzzy credibility-based optimization model with the Hurwicz criterion under uncertainty," Agricultural Water Management, Elsevier, vol. 254(C).
    11. Li, Mo & Guo, Ping & Singh, Vijay P., 2016. "An efficient irrigation water allocation model under uncertainty," Agricultural Systems, Elsevier, vol. 144(C), pages 46-57.
    12. Yang, Gaiqiang & Li, Xia & Huo, Lijuan & Liu, Qi, 2020. "A solving approach for fuzzy multi-objective linear fractional programming and application to an agricultural planting structure optimization problem," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    13. Kang, Shaozhong & Hao, Xinmei & Du, Taisheng & Tong, Ling & Su, Xiaoling & Lu, Hongna & Li, Xiaolin & Huo, Zailin & Li, Sien & Ding, Risheng, 2017. "Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice," Agricultural Water Management, Elsevier, vol. 179(C), pages 5-17.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mardani Najafabadi, Mostafa & Magazzino, Cosimo & Valente, Donatella & Mirzaei, Abbas & Petrosillo, Irene, 2023. "A new interval meta-goal programming for sustainable planning of agricultural water-land use nexus," Ecological Modelling, Elsevier, vol. 484(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Chenglong & Guo, Ping & Huo, Zailin, 2021. "Irrigation water resources management under uncertainty: An interval nonlinear double-sided fuzzy chance-constrained programming approach," Agricultural Water Management, Elsevier, vol. 245(C).
    2. Zhang, Chenglong & Engel, Bernard A. & Guo, Ping, 2018. "An Interval-based Fuzzy Chance-constrained Irrigation Water Allocation model with double-sided fuzziness," Agricultural Water Management, Elsevier, vol. 210(C), pages 22-31.
    3. Li, Xuemin & Zhang, Chenglong & Huo, Zailin & Adeloye, Adebayo J., 2020. "A sustainable irrigation water management framework coupling water-salt processes simulation and uncertain optimization in an arid area," Agricultural Water Management, Elsevier, vol. 231(C).
    4. Zhang, Chenglong & Li, Xuemin & Guo, Ping & Huo, Zailin, 2020. "An improved interval-based fuzzy credibility-constrained programming approach for supporting optimal irrigation water management under uncertainty," Agricultural Water Management, Elsevier, vol. 238(C).
    5. Zhang, Fengtai & Xiao, Yuedong & Gao, Lei & Ma, Dalai & Su, Ruiqi & Yang, Qing, 2022. "How agricultural water use efficiency varies in China—A spatial-temporal analysis considering unexpected outputs," Agricultural Water Management, Elsevier, vol. 260(C).
    6. Niu, Geng & Zheng, Yi & Han, Feng & Qin, Huapeng, 2019. "The nexus of water, ecosystems and agriculture in arid areas: A multiobjective optimization study on system efficiencies," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    7. Li, Mo & Cao, Xiaoxu & Liu, Dong & Fu, Qiang & Li, Tianxiao & Shang, Ruochen, 2022. "Sustainable management of agricultural water and land resources under changing climate and socio-economic conditions: A multi-dimensional optimization approach," Agricultural Water Management, Elsevier, vol. 259(C).
    8. Li, Zhong & Huang, Gordon & Zhang, Yimei & Li, Yongping, 2013. "Inexact two-stage stochastic credibility constrained programming for water quality management," Resources, Conservation & Recycling, Elsevier, vol. 73(C), pages 122-132.
    9. Yue, Qiong & Zhang, Fan & Zhang, Chenglong & Zhu, Hua & Tang, Yikuan & Guo, Ping, 2020. "A full fuzzy-interval credibility-constrained nonlinear programming approach for irrigation water allocation under uncertainty," Agricultural Water Management, Elsevier, vol. 230(C).
    10. Chongfeng Ren & Jiantao Yang & Hongbo Zhang, 2019. "An inexact fractional programming model for irrigation water resources optimal allocation under multiple uncertainties," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-17, June.
    11. Chongfeng Ren & Ruihuan Li & Ping Guo, 2016. "Two-Stage DEA Analysis of Water Resource Use Efficiency," Sustainability, MDPI, vol. 9(1), pages 1-17, December.
    12. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Cheraghi, Sara, 2020. "Robust and stable flexible blood supply chain network design under motivational initiatives," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    13. Mardani Najafabadi, Mostafa & Magazzino, Cosimo & Valente, Donatella & Mirzaei, Abbas & Petrosillo, Irene, 2023. "A new interval meta-goal programming for sustainable planning of agricultural water-land use nexus," Ecological Modelling, Elsevier, vol. 484(C).
    14. Zhang, Yi Mei & Huang, Guo He, 2011. "Inexact credibility constrained programming for environmental system management," Resources, Conservation & Recycling, Elsevier, vol. 55(4), pages 441-447.
    15. Khezrimotlagh, Dariush & Kaffash, Sepideh & Zhu, Joe, 2022. "U.S. airline mergers’ performance and productivity change," Journal of Air Transport Management, Elsevier, vol. 102(C).
    16. Christian Growitsch & Tooraj Jamasb & Christine Müller & Matthias Wissner, 2016. "Social Cost Efficient Service Quality: Integrating Customer Valuation in Incentive Regulation—Evidence from the Case of Norway," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 71-91, Springer.
    17. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, February.
    18. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    19. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    20. repec:lan:wpaper:1115 is not listed on IDEAS
    21. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:277:y:2023:i:c:s0378377422006825. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.