IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v245y2021ics0378377420322022.html
   My bibliography  Save this article

Irrigation water resources management under uncertainty: An interval nonlinear double-sided fuzzy chance-constrained programming approach

Author

Listed:
  • Zhang, Chenglong
  • Guo, Ping
  • Huo, Zailin

Abstract

An interval nonlinear double-sided fuzzy chance-constrained programming (INDFCCP) approach is formulated to effectively allocate irrigation water among competing water users. The INDFCCP approach is formulated by combining inexact quadratic programming (IQP) and double-sided fuzzy chance-constrained programming (DFCCP) within a general optimization framework. This approach has the following features. (1) It’s able to handle interval and fuzzy uncertainties, and nonlinearity existing in the objective functions. (2) It’s capable of addressing these fuzzy constraints and fuzzy variables where different confidence levels and satisfaction degree levels should be satisfied. (3) Each fuzzy chance-constraint can be further analyzed with the maximum and minimum reliability scenarios, which makes it possible to reflect variations of system conditions. (4) Interval quadratic crop water production functions (IQCWPFs) are employed in place of deterministic ones to quantitatively describe the mathematical relationships between crop yields and actual crop evapotranspiration (or irrigation water applied). Then, to demonstrate its applicability and feasibility, the INDFCCP approach is applied in the Yingke Irrigation District (YID), northwest China for allocating irrigation water to three crops in three subareas under uncertainty. Finally, more flexible decision solutions regarding optimal irrigation water allocation have been generated and analyzed under different predetermined confidence levels, showing several advantages of the INDFCCP approach with respect to the deterministic one. Under the same confidence level, system benefits under the minimum reliability scenario (e.g. [499.6, 909.7] × 106 Yuan, α = 0.5) are higher than that under the maximum reliability scenario (e.g. [498.7, 908.9] × 106 Yuan, α = 0.5). From above outcomes, the INDFCCP approach provides more appropriate results and reliable scientific bases needed for better managing irrigation water in irrigated agricultural areas.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:agiwat:v:245:y:2021:i:c:s0378377420322022
    DOI: 10.1016/j.agwat.2020.106658
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377420322022
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2020.106658?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. Geerts, Sam & Raes, Dirk, 2009. "Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas," Agricultural Water Management, Elsevier, vol. 96(9), pages 1275-1284, September.
    2. Zhang, Heping & Oweis, Theib, 1999. "Water-yield relations and optimal irrigation scheduling of wheat in the Mediterranean region," Agricultural Water Management, Elsevier, vol. 38(3), pages 195-211, January.
    3. 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.
    4. 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.
    5. 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.
    6. Chen, F. & Huang, G.H. & Fan, Y.R. & Chen, J.P., 2017. "A copula-based fuzzy chance-constrained programming model and its application to electric power generation systems planning," Applied Energy, Elsevier, vol. 187(C), pages 291-309.
    7. 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.
    8. 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.
    9. Jiang, Yao & Xu, Xu & Huang, Quanzhong & Huo, Zailin & Huang, Guanhua, 2015. "Assessment of irrigation performance and water productivity in irrigated areas of the middle Heihe River basin using a distributed agro-hydrological model," Agricultural Water Management, Elsevier, vol. 147(C), pages 67-81.
    10. Chen, M. J. & Huang, G. H., 2001. "A derivative algorithm for inexact quadratic program - application to environmental decision-making under uncertainty," European Journal of Operational Research, Elsevier, vol. 128(3), pages 570-586, February.
    11. Brumbelow, Kelly & Georgakakos, Aris, 2007. "Determining crop-water production functions using yield-irrigation gradient algorithms," Agricultural Water Management, Elsevier, vol. 87(2), pages 151-161, January.
    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. Liu, Yanqi & Lin, Yifan & Huo, Zailin & Zhang, Chenglong & Wang, Chaozi & Xue, Jingyuan & Huang, Guanhua, 2022. "Spatio-temporal variation of irrigation water requirements for wheat and maize in the Yellow River Basin, China, 1974–2017," Agricultural Water Management, Elsevier, vol. 262(C).
    2. Guo, Yating & Ye, Guoju & Liu, Wei & Zhao, Dafang & Treanţǎ, Savin, 2023. "Solving nonsmooth interval optimization problems based on interval-valued symmetric invexity," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    3. Kun Jia & Wei Zhang & Bingyan Xie & Xitong Xue & Feng Zhang & Dongrui Han, 2022. "Does Climate Change Increase Crop Water Requirements of Winter Wheat and Summer Maize in the Lower Reaches of the Yellow River Basin?," IJERPH, MDPI, vol. 19(24), pages 1-12, December.
    4. Wang, Shuping & Tan, Qian & Zhang, Tianyuan & Zhang, Tong, 2022. "Water management policy analysis: Insight from a calibration-based inexact programming method," Agricultural Water Management, Elsevier, vol. 269(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 & 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).
    2. Foster, T. & Brozović, N., 2018. "Simulating Crop-Water Production Functions Using Crop Growth Models to Support Water Policy Assessments," Ecological Economics, Elsevier, vol. 152(C), pages 9-21.
    3. 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).
    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. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    6. 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.
    7. Peake, A.S. & Carberry, P.S. & Raine, S.R. & Gett, V. & Smith, R.J., 2016. "An alternative approach to whole-farm deficit irrigation analysis: Evaluating the risk-efficiency of wheat irrigation strategies in sub-tropical Australia," Agricultural Water Management, Elsevier, vol. 169(C), pages 61-76.
    8. Wang, Youzhi & Guo, Shanshan & Yue, Qing & Mao, Xiaomin & Guo, Ping, 2021. "Distributed AquaCrop simulation-nonlinear multi-objective dependent-chance programming for irrigation water resources management under uncertainty," Agricultural Water Management, Elsevier, vol. 247(C).
    9. 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.
    10. 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.
    11. Knowling, Matthew J. & Walker, Rob R. & Pellegrino, Anne & Edwards, Everard J. & Westra, Seth & Collins, Cassandra & Ostendorf, Bertram & Bennett, Bree, 2023. "Generalized water production relations through process-based modeling: A viticulture example," Agricultural Water Management, Elsevier, vol. 280(C).
    12. Liu Liu & Zezhong Guo & Guanhua Huang & Ruotong Wang, 2019. "Water Productivity Evaluation under Multi-GCM Projections of Climate Change in Oases of the Heihe River Basin, Northwest China," IJERPH, MDPI, vol. 16(10), pages 1-17, May.
    13. Chenglong Zhang & Qiong Yue & Ping Guo, 2019. "A Nonlinear Inexact Two-Stage Management Model for Agricultural Water Allocation under Uncertainty Based on the Heihe River Water Diversion Plan," IJERPH, MDPI, vol. 16(11), pages 1-18, May.
    14. Yu, L. & Li, Y.P. & Huang, G.H. & Fan, Y.R. & Yin, S., 2018. "Planning regional-scale electric power systems under uncertainty: A case study of Jing-Jin-Ji region, China," Applied Energy, Elsevier, vol. 212(C), pages 834-849.
    15. Mustafa, S.M.T. & Vanuytrecht, E. & Huysmans, M., 2017. "Combined deficit irrigation and soil fertility management on different soil textures to improve wheat yield in drought-prone Bangladesh," Agricultural Water Management, Elsevier, vol. 191(C), pages 124-137.
    16. Yang, Chenyao & Fraga, Helder & Ieperen, Wim Van & Santos, João Andrade, 2017. "Assessment of irrigated maize yield response to climate change scenarios in Portugal," Agricultural Water Management, Elsevier, vol. 184(C), pages 178-190.
    17. Geerts, S. & Raes, D. & Garcia, M. & Taboada, C. & Miranda, R. & Cusicanqui, J. & Mhizha, T. & Vacher, J., 2009. "Modeling the potential for closing quinoa yield gaps under varying water availability in the Bolivian Altiplano," Agricultural Water Management, Elsevier, vol. 96(11), pages 1652-1658, November.
    18. Zhang, Bangbang & Feng, Gary & Ahuja, Lajpat R. & Kong, Xiangbin & Ouyang, Ying & Adeli, Ardeshir & Jenkins, Johnie N., 2018. "Soybean crop-water production functions in a humid region across years and soils determined with APEX model," Agricultural Water Management, Elsevier, vol. 204(C), pages 180-191.
    19. Arman Ganji & Sara Kaviani, 2013. "Probability Analysis of Crop Water Stress Index: An Application of Double Bounded Density Function (DB-CDF)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(10), pages 3791-3802, August.
    20. Komlan Koudahe & Aleksey Y. Sheshukov & Jonathan Aguilar & Koffi Djaman, 2021. "Irrigation-Water Management and Productivity of Cotton: A Review," Sustainability, MDPI, vol. 13(18), pages 1-21, September.

    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:245:y:2021:i:c:s0378377420322022. 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.