IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i6p853-d837510.html
   My bibliography  Save this article

Agricultural Water Optimal Allocation Using Minimum Cross-Entropy and Entropy-Weight-Based TOPSIS Method in Hetao Irrigation District, Northwest China

Author

Listed:
  • Yunquan Zhang

    (Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China)

  • Peiling Yang

    (Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China)

Abstract

Affected by the temporal and spatial changes of natural resources, human activities, and social economic system policies, there are many uncertainties in the development, utilization, and management process of irrigation district agricultural water resources, which will increase the complexity of the use of irrigation district agricultural water resources. Decision makers find it challenging to cope with the complexity of fluctuating water supplies and demands that are critical for water resources’ allocation. In response to these issues, this paper presents an optimization modeling approach for agricultural water allocation at an irrigation district scale, considering the uncertainties of water supply and demand. The minimum cross-entropy method was used to estimate the parameters of hydrologic frequency distribution functions of water supply and demand, which are the basis for agricultural water resources’ optimal allocation and the evaluation of water resources’ carrying capacity in the Hetao Irrigation District. Interval Linear Fractional Programming was used to find water availability, shortage, and use efficiency in different irrigation areas of the Hetao Irrigation District (HID) under different scenarios. The denominator of fractional planning is the environmental goal, and the numerator is the economic goal; so, the objective function of fractional programming is the utility rate required in the post-optimization analysis. Future water availability and shortage scenarios are adopted consistent with the Representative Concentration Pathways’ (RCPs’) framework, and future water use scenarios are developed using the Shared Socioeconomic Pathways’ (SSPs’) framework. Results revealed that under SSP1, the annual water consumption increased from 30 billion m 3 to 60 billion m 3 , almost doubling in Urad. The annual water consumption under SSP2 and SSP3 increased slightly, from 30 billion m 3 to about 50 billion m 3 . The amount of water available for well irrigation in Urad decreased from 300 to 250 billion m 3 , while the amount of water available for canal irrigation in Urad remained at 270 billion m 3 from 2010 s to 2030 s, only dropping to 240 billion m 3 in 2040 s. The entropy-weight-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method was applied to evaluate agricultural water resources’ allocation schemes because it can avoid the subjectivity of weight determination and can reflect the dynamic changing trend of irrigation district agricultural water resources’ carrying capacity. The approach is applicable to most regions, such as the Hetao Irrigation District in the Upper Yellow River Basi with limited precipitation, to determine water strategies under the changing environment.

Suggested Citation

  • Yunquan Zhang & Peiling Yang, 2022. "Agricultural Water Optimal Allocation Using Minimum Cross-Entropy and Entropy-Weight-Based TOPSIS Method in Hetao Irrigation District, Northwest China," Agriculture, MDPI, vol. 12(6), pages 1-18, June.
  • Handle: RePEc:gam:jagris:v:12:y:2022:i:6:p:853-:d:837510
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/6/853/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/12/6/853/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Caixia & Rubæk, Gitte H. & Liu, Fulai & Andersen, Mathias N., 2015. "Effect of partial root zone drying and deficit irrigation on nitrogen and phosphorus uptake in potato," Agricultural Water Management, Elsevier, vol. 159(C), pages 66-76.
    2. Liudong Zhang & Ping Guo & Shiqi Fang & Mo Li, 2014. "Monthly Optimal Reservoirs Operation for Multicrop Deficit Irrigation under Fuzzy Stochastic Uncertainties," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-11, March.
    3. Q. Tan & G. Huang & Y. Cai, 2013. "Multi-Source Multi-Sector Sustainable Water Supply Under Multiple Uncertainties: An Inexact Fuzzy-Stochastic Quadratic Programming Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(2), pages 451-473, January.
    4. Zhang, Dongmei & Guo, Ping, 2016. "Integrated agriculture water management optimization model for water saving potential analysis," Agricultural Water Management, Elsevier, vol. 170(C), pages 5-19.
    5. Shiqi Fang & Ping Guo & Mo Li & Liudong Zhang, 2013. "Bilevel Multiobjective Programming Applied to Water Resources Allocation," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-9, March.
    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. Yunquan Zhang & Peiling Yang, 2023. "A Simulation-Based Optimization Model for Control of Soil Salinization in the Hetao Irrigation District, Northwest China," Sustainability, MDPI, vol. 15(5), pages 1-20, March.

    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. Bao-Li Miao & Ying Liu & Yu-Bing Fan & Xue-Jiao Niu & Xiu-Yun Jiang & Zeng Tang, 2023. "Optimization of Agricultural Resource Allocation among Crops: A Portfolio Model Analysis," Land, MDPI, vol. 12(10), pages 1-18, October.
    2. Zhang, Cheng-Yao & Oki, Taikan, 2023. "Water pricing reform for sustainable water resources management in China’s agricultural sector," Agricultural Water Management, Elsevier, vol. 275(C).
    3. Luís Loures & José Gama & José Rato Nunes & António Lopez-Piñeiro, 2017. "Assessing the Sodium Exchange Capacity in Rainfed and Irrigated Soils in the Mediterranean Basin Using GIS," Sustainability, MDPI, vol. 9(3), pages 1-12, March.
    4. Sangha, Laljeet & Shortridge, Julie & Frame, William, 2023. "The impact of nitrogen treatment and short-term weather forecast data in irrigation scheduling of corn and cotton on water and nutrient use efficiency in humid climates," Agricultural Water Management, Elsevier, vol. 283(C).
    5. Wenlan Ke & Jinghua Sha & Jingjing Yan & Guofeng Zhang & Rongrong Wu, 2016. "A Multi-Objective Input–Output Linear Model for Water Supply, Economic Growth and Environmental Planning in Resource-Based Cities," Sustainability, MDPI, vol. 8(2), pages 1-18, February.
    6. Wei, Jun & Cui, Yuanlai & Zhou, Sihang & Luo, Yufeng, 2022. "Regional water-saving potential calculation method for paddy rice based on remote sensing," Agricultural Water Management, Elsevier, vol. 267(C).
    7. Shannak, Sa'd, 2022. "Optimizing dynamics of water-energy-food nexus in a desert climate," Energy Policy, Elsevier, vol. 164(C).
    8. Wang, Yaosheng & Janz, Baldur & Engedal, Tine & Neergaard, Andreas de, 2017. "Effect of irrigation regimes and nitrogen rates on water use efficiency and nitrogen uptake in maize," Agricultural Water Management, Elsevier, vol. 179(C), pages 271-276.
    9. Liu, Xuezhi & Manevski, Kiril & Liu, Fulai & Andersen, Mathias Neumann, 2022. "Biomass accumulation and water use efficiency of faba bean-ryegrass intercropping system on sandy soil amended with biochar under reduced irrigation regimes," Agricultural Water Management, Elsevier, vol. 273(C).
    10. Lijun Jiao & Ruimin Liu & Linfang Wang & Lin Li & Leiping Cao, 2021. "Evaluating Spatiotemporal Variations in the Impact of Inter-basin Water Transfer Projects in Water-receiving Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(15), pages 5409-5429, December.
    11. Liu, Qi & Niu, Jun & Wood, Jeffrey D. & Kang, Shaozhong, 2022. "Spatial optimization of cropping pattern in the upper-middle reaches of the Heihe River basin, Northwest China," Agricultural Water Management, Elsevier, vol. 264(C).
    12. Gao, Jie & Zhuo, La & Duan, Ximing & Wu, Pute, 2023. "Agricultural water-saving potentials with water footprint benchmarking under different tillage practices for crop production in an irrigation district," Agricultural Water Management, Elsevier, vol. 282(C).
    13. 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.
    14. Luo, Jianmei & Zhang, Hongmei & Qi, Yongqing & Pei, Hongwei & Shen, Yanjun, 2022. "Balancing water and food by optimizing the planting structure in the Beijing–Tianjin–Hebei region, China," Agricultural Water Management, Elsevier, vol. 262(C).
    15. Chen, Mengting & Luo, Yufeng & Shen, Yingying & Han, Zhenzhong & Cui, Yuanlai, 2020. "Driving force analysis of irrigation water consumption using principal component regression analysis," Agricultural Water Management, Elsevier, vol. 234(C).
    16. C. Dai & Y. Cai & Y. Liu & W. Wang & H. Guo, 2015. "A Generalized Interval Fuzzy Chance-Constrained Programming Method for Domestic Wastewater Management Under Uncertainty – A Case Study of Kunming, 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 3015-3036, July.
    17. Luís Loures & Alejandro Chamizo & Paulo Ferreira & Ana Loures & Rui Castanho & Thomas Panagopoulos, 2020. "Assessing the Effectiveness of Precision Agriculture Management Systems in Mediterranean Small Farms," Sustainability, MDPI, vol. 12(9), pages 1-15, May.
    18. Z. Ghaffari Moghadam & E. Moradi & M. Hashemi Tabar & A. Sardar Shahraki, 2023. "Developing a Bi-level programming model for water allocation based on Nerlove’s supply response theory and water market," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(6), pages 5663-5689, June.
    19. Wang, Xiukang & Guo, Tao & Wang, Yi & Xing, Yingying & Wang, Yanfeng & He, Xiaolong, 2020. "Exploring the optimization of water and fertilizer management practices for potato production in the sandy loam soils of Northwest China based on PCA," Agricultural Water Management, Elsevier, vol. 237(C).
    20. Giovanni Pino & Pierluigi Toma & Cristian Rizzo & Pier Paolo Miglietta & Alessandro M. Peluso & Gianluigi Guido, 2017. "Determinants of Farmers’ Intention to Adopt Water Saving Measures: Evidence from Italy," Sustainability, MDPI, vol. 9(1), pages 1-14, January.

    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:jagris:v:12:y:2022:i:6:p:853-:d:837510. 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.