IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i21p11652-d673421.html
   My bibliography  Save this article

Multi-Objective Optimal Allocation of River Basin Water Resources under Full Probability Scenarios Considering Wet–Dry Encounters: A Case Study of Yellow River Basin

Author

Listed:
  • Xike Guan

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

  • Zengchuan Dong

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

  • Yun Luo

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

  • Dunyu Zhong

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

Abstract

Wet–dry encounters between basins and regions have an important impact on the allocation of water resources. This study proposes a multi-objective allocation model for basin water resources under full probability scenarios considering wet–dry encounters (FPS-MOWAM) to solve the problem of basin water resource allocation. In the FPS-MOWAM model, the sub-regions were merged by precipitation correlation analysis. Next, the joint probability distribution of basin runoff and region precipitation was constructed using copula functions. The possible wet–dry encounter scenarios and their probabilities were then acquired. Finally, the multi-objective allocation model of water resources was constructed using the full probability scenario for wet–dry encounters in each region. The FPS-MOWAM is calculated by the NSGA-II algorithm and the optimal water resource allocation scheme was selected using the fuzzy comprehensive evaluation method. Using the Yellow River Basin as an example, the following conclusions were obtained: (1) the Yellow River Basin can be divided into four sub-regions based on precipitation correlations: Qh-Sc (Qinghai, Sichuan), Sg-Nx-Nmg (Gansu, Ningxia, Inner Mongolia), Sxq-Sxj (Shaanxi, Shanxi), and Hn-Sd (Henan, Shandong), (2) the inconsistencies in synchronous–asynchronous encounter probabilities in the Yellow River Basin were significant (the asynchronous probabilities were 0.763), whereas the asynchronous probabilities among the four regions were 0.632, 0.932, and 0.763 under the high, medium, and low flow conditions in the Yellow River Basin respectively, and (3) the allocation of water resources tends to increase with time, allocating the most during dry years. In 2035, the expected economic benefits are between 11,982.7 billion CNY and 12,499.6 billion CNY, while the expected water shortage rate is between 2.02% and 3.43%. In 2050, the expected economic benefits are between 21,291.4 billion CNY and 21,781.3 billion CNY, while the expected water shortage rate is between 1.28% and 6.05%.

Suggested Citation

  • Xike Guan & Zengchuan Dong & Yun Luo & Dunyu Zhong, 2021. "Multi-Objective Optimal Allocation of River Basin Water Resources under Full Probability Scenarios Considering Wet–Dry Encounters: A Case Study of Yellow River Basin," IJERPH, MDPI, vol. 18(21), pages 1-19, November.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:21:p:11652-:d:673421
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/21/11652/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/21/11652/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jitao Zhang & Zengchuan Dong & Tian Chen, 2020. "Multi-Objective Optimal Allocation of Water Resources Based on the NSGA-2 Algorithm While Considering Intergenerational Equity: A Case Study of the Middle and Upper Reaches of Huaihe River Basin, Chin," IJERPH, MDPI, vol. 17(24), pages 1-18, December.
    2. Leszek Sobkowiak & Adam Perz & Dariusz Wrzesiński & Muhammad Abrar Faiz, 2020. "Estimation of the River Flow Synchronicity in the Upper Indus River Basin Using Copula Functions," Sustainability, MDPI, vol. 12(12), pages 1-18, June.
    3. Xuan, Wang & Quan, Cui & Shuyi, Li, 2012. "An optimal water allocation model based on water resources security assessment and its application in Zhangjiakou Region, northern China," Resources, Conservation & Recycling, Elsevier, vol. 69(C), pages 57-65.
    4. H. Wang & Y. Dong & Y. Wang & Q. Liu, 2008. "Water Right Institution and Strategies of the Yellow River Valley," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(10), pages 1499-1519, October.
    5. M. Babel & A. Gupta & D. Nayak, 2005. "A Model for Optimal Allocation of Water to Competing Demands," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(6), pages 693-712, December.
    6. Tsai, Wen-Ping & Cheng, Chung-Lien & Uen, Tinn-Shuan & Zhou, Yanlai & Chang, Fi-John, 2019. "Drought mitigation under urbanization through an intelligent water allocation system," Agricultural Water Management, Elsevier, vol. 213(C), pages 87-96.
    7. Morais, Danielle C. & de Almeida, Adiel Teixeira, 2012. "Group decision making on water resources based on analysis of individual rankings," Omega, Elsevier, vol. 40(1), pages 42-52, January.
    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. J. Shiau, 2006. "Fitting Drought Duration and Severity with Two-Dimensional Copulas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(5), pages 795-815, October.
    10. Li, Mo & Fu, Qiang & Singh, Vijay P. & Liu, Dong, 2018. "An interval multi-objective programming model for irrigation water allocation under uncertainty," Agricultural Water Management, Elsevier, vol. 196(C), pages 24-36.
    Full references (including those not matched with items on IDEAS)

    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. Elleuch, Mohamed Ali & Anane, Makram & Euchi, Jalel & Frikha, Ahmed, 2019. "Hybrid fuzzy multi-criteria decision making to solve the irrigation water allocation problem in the Tunisian case," Agricultural Systems, Elsevier, vol. 176(C).
    2. Jing Tian & Shenglian Guo & Dedi Liu & Zhengke Pan & Xingjun Hong, 2019. "A Fair Approach for Multi-Objective Water Resources Allocation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(10), pages 3633-3653, August.
    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. 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.
    5. Guo, Daxin & Olesen, Jørgen Eivind & Manevski, Kiril & Ma, Xiaoyi, 2021. "Optimizing irrigation schedule in a large agricultural region under different hydrologic scenarios," Agricultural Water Management, Elsevier, vol. 245(C).
    6. Ming Li & Guiwen Wang & Shengwei Zong & Xurong Chai, 2023. "Copula-Based Assessment and Regionalization of Drought Risk in China," IJERPH, MDPI, vol. 20(5), pages 1-16, February.
    7. Hu, Zhineng & Chen, Yazhen & Yao, Liming & Wei, Changting & Li, Chaozhi, 2016. "Optimal allocation of regional water resources: From a perspective of equity–efficiency tradeoff," Resources, Conservation & Recycling, Elsevier, vol. 109(C), pages 102-113.
    8. Ziqiang Xing & Denghua Yan & Cheng Zhang & Gang Wang & Dongdong Zhang, 2015. "Spatial Characterization and Bivariate Frequency Analysis of Precipitation and Runoff in the Upper Huai River Basin, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3291-3304, July.
    9. Pang, Jifang & Liang, Jiye, 2012. "Evaluation of the results of multi-attribute group decision-making with linguistic information," Omega, Elsevier, vol. 40(3), pages 294-301.
    10. F. Todisco & F. Mannocchi & L. Vergni, 2013. "Severity–duration–frequency curves in the mitigation of drought impact: an agricultural case study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(3), pages 1863-1881, February.
    11. Katarzyna Baran-Gurgul, 2022. "The Risk of Extreme Streamflow Drought in the Polish Carpathians—A Two-Dimensional Approach," IJERPH, MDPI, vol. 19(21), pages 1-27, October.
    12. Leakey, Roger & Kranjac-Berisavljevic, Gordana & Caron, Patrick & Craufurd, Peter & Martin, Adrienne M. & McDonald, Andy & Abedini, Walter & Afiff, Suraya & Bakurin, Ndey & Bass, Steve & Hilbeck, Ange, 2009. "Impacts of AKST on development and sustainability goals," Book Chapters,, International Water Management Institute.
    13. Fatih Tosunoglu & Ibrahim Can, 2016. "Application of copulas for regional bivariate frequency analysis of meteorological droughts in Turkey," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(3), pages 1457-1477, July.
    14. Zahra Sadat Hosseini & Mahnoosh Moghaddasi & Shahla Paimozd, 2023. "Simultaneous Monitoring of Different Drought Types Using Linear and Nonlinear Combination Approaches," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1125-1151, February.
    15. Serafim Opricovic, 2009. "A Compromise Solution in Water Resources Planning," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(8), pages 1549-1561, June.
    16. Jie Yang & Yimin Wang & Jun Yao & Jianxia Chang & Guoxin Xu & Xin Wang & Hui Hu, 2020. "Coincidence probability analysis of hydrologic low-flow under the changing environment in the Wei River Basin," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(2), pages 1711-1726, September.
    17. Chunlong Li & Jianzhong Zhou & Shuo Ouyang & Chao Wang & Yi Liu, 2015. "Water Resources Optimal Allocation Based on Large-scale Reservoirs in the Upper Reaches of Yangtze River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2171-2187, May.
    18. Jing Tian & Dedi Liu & Shenglian Guo & Zhengke Pan & Xingjun Hong, 2019. "Impacts of Inter-Basin Water Transfer Projects on Optimal Water Resources Allocation in the Hanjiang River Basin, China," Sustainability, MDPI, vol. 11(7), pages 1-19, April.
    19. Zuo, Qiting & Wu, Qingsong & Yu, Lei & Li, Yongping & Fan, Yurui, 2021. "Optimization of uncertain agricultural management considering the framework of water, energy and food," Agricultural Water Management, Elsevier, vol. 253(C).
    20. Liuyue He & Sufen Wang & Congcong Peng & Qian Tan, 2018. "Optimization of Water Consumption Distribution Based on Crop Suitability in the Middle Reaches of Heihe River," Sustainability, MDPI, vol. 10(7), pages 1-17, June.

    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:gam:jijerp:v:18:y:2021:i:21:p:11652-:d:673421. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.