IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i20p5567-d274864.html
   My bibliography  Save this article

Agricultural Water Management Model Based on Grey Water Footprints under Uncertainty and its Application

Author

Listed:
  • Ge Song

    (College of Water Resources & Civil Engineering, China Agricultural University, Beijing 100083, China
    State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China)

  • Chao Dai

    (School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore)

  • Qian Tan

    (College of Water Resources & Civil Engineering, China Agricultural University, Beijing 100083, China
    Institute of Environmental and Ecological Engineering, Guangdong University of Technology, Guangzhou 510006, China)

  • Shan Zhang

    (College of Water Resources & Civil Engineering, China Agricultural University, Beijing 100083, China)

Abstract

The grey water footprint theory was introduced into a fractional programming model to alleviate non-point source pollution and increase water-use efficiency through the adjustment of crop planting structure. The interval programming method was also incorporated within the developed framework to handle parametric uncertainties. The objective function of the model was the ratio of economic benefits to grey water footprints from crop production, and the constraints contained water availability constraints, food security constraints, planting area constraints, grey water footprint constraints and non-negative constraints. The model was applied to the Hetao Irrigation District of China. It was found that, based on the data in the year of 2016, the optimal planting plans generated from the developed model would reduce 34,400 m 3 of grey water footprints for every 100 million Yuan gained from crops. Under the optimal planting structure, the total grey water footprints would be reduced by 21.9 million m 3 , the total economic benefits from crops would be increased by 1.138 billion Yuan, and the irrigation water would be saved by 44 million m 3 . The optimal results could provide decision-makers with agricultural water use plans with reduced negative impacts on the environment and enhanced economic benefits from crops.

Suggested Citation

  • Ge Song & Chao Dai & Qian Tan & Shan Zhang, 2019. "Agricultural Water Management Model Based on Grey Water Footprints under Uncertainty and its Application," Sustainability, MDPI, vol. 11(20), pages 1-18, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:20:p:5567-:d:274864
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/20/5567/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/20/5567/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhu, H. & Huang, W.W. & Huang, G.H., 2014. "Planning of regional energy systems: An inexact mixed-integer fractional programming model," Applied Energy, Elsevier, vol. 113(C), pages 500-514.
    2. Ozdemir, Mujgan S. & Saaty, Thomas L., 2006. "The unknown in decision making: What to do about it," European Journal of Operational Research, Elsevier, vol. 174(1), pages 349-359, October.
    3. Irina Marinov & Anca Marinov, 2014. "A Coupled Mathematical Model to Predict the Influence of Nitrogen Fertilization on Crop, Soil and Groundwater Quality," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5231-5246, December.
    4. Marina Segura & Concepción Maroto & Concepción Ginestar & Baldomero Segura, 2018. "Optimization Models to Improve Estimations and Reduce Nitrogen Excretion from Livestock Production," Sustainability, MDPI, vol. 10(7), pages 1-14, July.
    5. Qiuchi Xue & Xin Yang & Jianjun Wu & Huijun Sun & Haodong Yin & Yunchao Qu, 2019. "Urban Rail Timetable Optimization to Improve Operational Efficiency with Flexible Routing Plans: A Nonlinear Integer Programming Model," Sustainability, MDPI, vol. 11(13), pages 1-26, July.
    6. Eros Borsato & Alejandro Galindo & Paolo Tarolli & Luigi Sartori & Francesco Marinello, 2018. "Evaluation of the Grey Water Footprint Comparing the Indirect Effects of Different Agricultural Practices," Sustainability, MDPI, vol. 10(11), pages 1-15, November.
    7. C. Dai & Y. P. Cai & W. T. Lu & H. Liu & H. C. Guo, 2016. "Conjunctive Water Use Optimization for Watershed-Lake Water Distribution System under Uncertainty: a Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4429-4449, September.
    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. Zhang, Tong & Tan, Qian & Yu, Xiaoning & Zhang, Shan, 2020. "Synergy assessment and optimization for water-energy-food nexus: Modeling and application," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    2. Zhenquan Xiao & Polat Muhtar & Wenxiu Huo & Chaogao An & Ling Yang & Fengrong Zhang, 2021. "Spatial and Temporal Differentiation of the Tourism Water Footprint in Mainland China and Its Influencing Factors," Sustainability, MDPI, vol. 13(18), pages 1-23, September.
    3. Chunjiang An & Mengfan Cai & Christophe Guy, 2020. "Rural Sustainable Environmental Management," Sustainability, MDPI, vol. 12(16), pages 1-5, August.
    4. Hu, Kejia & Tan, Qian & Zhang, Tianyuan & Wang, Shuping, 2020. "Assessing technology portfolios of clean energy-driven desalination-irrigation systems with interval-valued intuitionistic fuzzy sets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(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. Changyu Zhou & Guohe Huang & Jiapei Chen, 2019. "A Type-2 Fuzzy Chance-Constrained Fractional Integrated Modeling Method for Energy System Management of Uncertainties and Risks," Energies, MDPI, vol. 12(13), pages 1-21, June.
    2. Tatevik Yezekyan & Marco Benetti & Giannantonio Armentano & Samuele Trestini & Luigi Sartori & Francesco Marinello, 2021. "Definition of Reference Models for Power, Mass, Working Width, and Price for Tillage Implements," Agriculture, MDPI, vol. 11(3), pages 1-15, February.
    3. María del Pino Palacios-Diaz & Juan Ramón Fernández-Vera & Jose Manuel Hernández-Moreno & Regla Amorós & Vanessa Mendoza-Grimón, 2023. "Effect of Irrigation Management and Water Quality on Soil and Sorghum bicolor Payenne Yield in Cape Verde," Agriculture, MDPI, vol. 13(1), pages 1-18, January.
    4. Changyu Zhou & Guohe Huang & Jiapei Chen, 2018. "A Multi-Objective Energy and Environmental Systems Planning Model: Management of Uncertainties and Risks for Shanxi Province, China," Energies, MDPI, vol. 11(10), pages 1-21, October.
    5. Anna Podlasek & Eugeniusz Koda & Magdalena Daria Vaverková, 2021. "The Variability of Nitrogen Forms in Soils Due to Traditional and Precision Agriculture: Case Studies in Poland," IJERPH, MDPI, vol. 18(2), pages 1-28, January.
    6. Ricardo F.M. Teixeira & Tiago Domingos, 2019. "Current Practice and Future Perspectives for Livestock Production and Industrial Ecology," Sustainability, MDPI, vol. 11(15), pages 1-5, August.
    7. Baležentis, Tomas & Streimikiene, Dalia, 2017. "Multi-criteria ranking of energy generation scenarios with Monte Carlo simulation," Applied Energy, Elsevier, vol. 185(P1), pages 862-871.
    8. Nie, S. & Huang, Charley Z. & Huang, G.H. & Li, Y.P. & Chen, J.P. & Fan, Y.R. & Cheng, G.H., 2016. "Planning renewable energy in electric power system for sustainable development under uncertainty – A case study of Beijing," Applied Energy, Elsevier, vol. 162(C), pages 772-786.
    9. Julian Canto-Perello & Maria P. Martinez-Garcia & Jorge Curiel-Esparza & Manuel Martin-Utrillas, 2015. "Implementing Sustainability Criteria for Selecting a Roof Assembly Typology in Medium Span Buildings," Sustainability, MDPI, vol. 7(6), pages 1-18, May.
    10. 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.
    11. Song, Tangnyu & Huang, Guohe & Zhou, Xiong & Wang, Xiuquan, 2018. "An inexact two-stage fractional energy systems planning model," Energy, Elsevier, vol. 160(C), pages 275-289.
    12. Jeonghyun Kim & Hojeong Park & Jong Ahn Chun & Sanai Li, 2018. "Adaptation Strategies under Climate Change for Sustainable Agricultural Productivity in Cambodia," Sustainability, MDPI, vol. 10(12), pages 1-18, December.
    13. Zhang, Lang & He, Deqiang & He, Yan & Liu, Bin & Chen, Yanjun & Shan, Sheng, 2022. "Real-time energy saving optimization method for urban rail transit train timetable under delay condition," Energy, Elsevier, vol. 258(C).
    14. Wang, Junqi & Cao, Hongjun, 2022. "Improving competitive strategic decisions of Chinese coal companies toward green transformation: A hybrid multi-criteria decision-making model," Resources Policy, Elsevier, vol. 75(C).
    15. Marcelo Werneck Barbosa & José M. Cansino, 2022. "A Water Footprint Management Construct in Agri-Food Supply Chains: A Content Validity Analysis," Sustainability, MDPI, vol. 14(9), pages 1-17, April.
    16. Y. R. Fan & G. H. Huang & Y. P. Li & X. Q. Wang & Z. Li, 2016. "Probabilistic Prediction for Monthly Streamflow through Coupling Stepwise Cluster Analysis and Quantile Regression Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5313-5331, November.
    17. Xu, Ye & Tan, Junyuan & Wang, Xu & Li, Wei & He, Xing & Hu, Xiaoguang & Fan, Yurui, 2022. "Synergetic management of water-energy-food nexus system and GHG emissions under multiple uncertainties: An inexact fractional fuzzy chance constraint programming method," Agricultural Water Management, Elsevier, vol. 262(C).
    18. Yang, Xin & Xue, Qiuchi & Ding, Meiling & Wu, Jianjun & Gao, Ziyou, 2021. "Short-term prediction of passenger volume for urban rail systems: A deep learning approach based on smart-card data," International Journal of Production Economics, Elsevier, vol. 231(C).
    19. Xuan Li & Toshiyuki Yamamoto & Tao Yan & Lili Lu & Xiaofei Ye, 2020. "First Train Timetabling for Urban Rail Transit Networks with Maximum Passenger Transfer Satisfaction," Sustainability, MDPI, vol. 12(10), pages 1-22, May.
    20. Mirakyan, Atom & Guio, R.D., 2014. "A methodology in innovative support of the integrated energy planning preparation and orientation phase," Energy, Elsevier, vol. 78(C), pages 916-927.

    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:jsusta:v:11:y:2019:i:20:p:5567-:d:274864. 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.