IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v182y2020ics0308521x19315550.html
   My bibliography  Save this article

Towards sustainable water management in an arid agricultural region: A multi-level multi-objective stochastic approach

Author

Listed:
  • Zhang, Fan
  • Guo, Shanshan
  • Liu, Xiao
  • Wang, Youzhi
  • Engel, Bernard A.
  • Guo, Ping

Abstract

Water-shortage crisis is threatening the food production and sustainable development around the world. Especially for arid agricultural regions, it is necessary to plan sustainable agricultural water management strategies for improving water use efficiency. But there are many complexities in it, such as multiple decision-making levels, objectives, water users and uncertainties. To effectively tackle these complexities, this study presents a novel optimization-modeling approach consisting of a multi-level multi-objective stochastic programming (MLMOSP) model and weighting quantification method for formulating sustainable water-allocation schemes in arid agricultural regions. The MLMOSP model incorporates multi-level programming, multi-objective programming, and stochastic expectation programming into a general framework. The proposed approach is capable of: 1) quantifying key factors affecting water-allocation systems through weighting quantification methods; 2) describing the main conflicting objectives of each decision-making level, including economic benefits, environment impacts, fairness, effectiveness, and crop yield; 3) considering tradeoffs among conflicting objectives, and 4) reflecting the leader-follower relationship under different scenarios of surface water availability at a regional scale and a monthly temporal resolution. The proposed approach is applied to a real-world case in a typical arid agricultural region of northwest China for verifying its validity. From this real-world case, it is found that: 1) optimization results corresponding to different flow-level scenarios of surface runoff can provide upper-, middle-, and lower-level decision makers with a set of decision alternatives to help identify the most appropriate management strategy; and 2) multiple model comparisons show that the MLMOSP approach can not only give more practical results guaranteeing the achievement of decision-making goals at different decision-making levels, but also help reduce groundwater extraction under different flow level scenarios of surface runoff.

Suggested Citation

  • Zhang, Fan & Guo, Shanshan & Liu, Xiao & Wang, Youzhi & Engel, Bernard A. & Guo, Ping, 2020. "Towards sustainable water management in an arid agricultural region: A multi-level multi-objective stochastic approach," Agricultural Systems, Elsevier, vol. 182(C).
    • Handle: RePEc:eee:agisys:v:182:y:2020:i:c:s0308521x19315550
    DOI: 10.1016/j.agsy.2020.102848
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X19315550
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2020.102848?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. Tang, Yikuan & Zhang, Fan & Wang, Sufen & Zhang, Xiaodong & Guo, Shanshan & Guo, Ping, 2019. "A distributed interval nonlinear multiobjective programming approach for optimal irrigation water management in an arid area," Agricultural Water Management, Elsevier, vol. 220(C), pages 13-26.
    2. Li, Y.P. & Liu, J. & Huang, G.H., 2014. "A hybrid fuzzy-stochastic programming method for water trading within an agricultural system," Agricultural Systems, Elsevier, vol. 123(C), pages 71-83.
    3. S. Jamshid Mousavi & Nasrin Rafiee Anzab & Bentolhoda Asl-Rousta & Joong Hoon Kim, 2017. "Multi-Objective Optimization-Simulation for Reliability-Based Inter-Basin Water Allocation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(11), pages 3445-3464, September.
    4. Chen, Shu & Shao, Dongguo & Gu, Wenquan & Xu, Baoli & Li, Haoxin & Fang, Longzhang, 2017. "An interval multistage water allocation model for crop different growth stages under inputs uncertainty," Agricultural Water Management, Elsevier, vol. 186(C), pages 86-97.
    5. Jiang, Yao & Xu, Xu & Huang, Quanzhong & Huo, Zailin & Huang, Guanhua, 2016. "Optimizing regional irrigation water use by integrating a two-level optimization model and an agro-hydrological model," Agricultural Water Management, Elsevier, vol. 178(C), pages 76-88.
    6. Wang, S. & Huang, G.H., 2015. "A multi-level Taguchi-factorial two-stage stochastic programming approach for characterization of parameter uncertainties and their interactions: An application to water resources management," European Journal of Operational Research, Elsevier, vol. 240(2), pages 572-581.
    7. Thomas L. Saaty, 1994. "How to Make a Decision: The Analytic Hierarchy Process," Interfaces, INFORMS, vol. 24(6), pages 19-43, December.
    8. Li, Mo & Fu, Qiang & Singh, Vijay P. & Liu, Dong & Li, Tianxiao & Zhou, Yan, 2020. "Managing agricultural water and land resources with tradeoff between economic, environmental, and social considerations: A multi-objective non-linear optimization model under uncertainty," Agricultural Systems, Elsevier, vol. 178(C).
    9. Zhang, Fan & Zhang, Chenglong & Yan, Zehao & Guo, Shanshan & Wang, Youzhi & Guo, Ping, 2018. "An interval nonlinear multiobjective programming model with fuzzy-interval credibility constraint for crop monthly water allocation," Agricultural Water Management, Elsevier, vol. 209(C), pages 123-133.
    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. 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).
    2. Veisi, Hadi & Deihimfard, Reza & Shahmohammadi, Alireza & Hydarzadeh, Yasoub, 2022. "Application of the analytic hierarchy process (AHP) in a multi-criteria selection of agricultural irrigation systems," Agricultural Water Management, Elsevier, vol. 267(C).
    3. Li, Xuemin & Zhang, Jingwen & Cai, Ximing & Huo, Zailin & Zhang, Chenglong, 2023. "Simulation-optimization based real-time irrigation scheduling: A human-machine interactive method enhanced by data assimilation," Agricultural Water Management, Elsevier, vol. 276(C).
    4. Zhang, Fan & Cai, Yanpeng & Tan, Qian & Wang, Xuan, 2021. "Spatial water footprint optimization of crop planting: A fuzzy multiobjective optimal approach based on MOD16 evapotranspiration products," Agricultural Water Management, Elsevier, vol. 256(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. Chongfeng Ren & Hongbo Zhang, 2019. "An Inexact Optimization Model for Crop Area Under Multiple Uncertainties," IJERPH, MDPI, vol. 16(14), pages 1-20, July.
    2. Zhang, Zepeng & Wang, Qingzheng & Guan, Qingyu & Xiao, Xiong & Mi, Jimin & Lv, Songjian, 2023. "Research on the optimal allocation of agricultural water and soil resources in the Heihe River Basin based on SWAT and intelligent optimization," Agricultural Water Management, Elsevier, vol. 279(C).
    3. Min Chen & Songhao Shang & Wei Li, 2020. "Integrated Modeling Approach for Sustainable Land-Water-Food Nexus Management," Agriculture, MDPI, vol. 10(4), pages 1-19, April.
    4. Yue, Qiong & Guo, Ping, 2021. "Managing agricultural water-energy-food-environment nexus considering water footprint and carbon footprint under uncertainty," Agricultural Water Management, Elsevier, vol. 252(C).
    5. Tang, Yikuan & Zhang, Fan & Wang, Sufen & Zhang, Xiaodong & Guo, Shanshan & Guo, Ping, 2019. "A distributed interval nonlinear multiobjective programming approach for optimal irrigation water management in an arid area," Agricultural Water Management, Elsevier, vol. 220(C), pages 13-26.
    6. 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).
    7. 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).
    8. Zhang, Fan & Cai, Yanpeng & Tan, Qian & Wang, Xuan, 2021. "Spatial water footprint optimization of crop planting: A fuzzy multiobjective optimal approach based on MOD16 evapotranspiration products," Agricultural Water Management, Elsevier, vol. 256(C).
    9. Li, Mo & Fu, Qiang & Singh, Vijay P. & Liu, Dong & Li, Tianxiao & Zhou, Yan, 2020. "Managing agricultural water and land resources with tradeoff between economic, environmental, and social considerations: A multi-objective non-linear optimization model under uncertainty," Agricultural Systems, Elsevier, vol. 178(C).
    10. Gong, Xinghui & Zhang, Hongbo & Ren, Chongfeng & Sun, Dongyong & Yang, Jiantao, 2020. "Optimization allocation of irrigation water resources based on crop water requirement under considering effective precipitation and uncertainty," Agricultural Water Management, Elsevier, vol. 239(C).
    11. Li, Jiang & Shang, Songhao & Jiang, Hongzhe & Song, Jian & Rahman, Khalil Ur & Adeloye, Adebayo J., 2021. "Simulation-based optimization for spatiotemporal allocation of irrigation water in arid region," Agricultural Water Management, Elsevier, vol. 254(C).
    12. Li, Mo & Sun, Hao & Liu, Dong & Singh, Vijay P. & Fu, Qiang, 2021. "Multi-scale modeling for irrigation water and cropland resources allocation considering uncertainties in water supply and demand," Agricultural Water Management, Elsevier, vol. 246(C).
    13. Madan K. Jha & Richard C. Peralta & Sasmita Sahoo, 2020. "Simulation-Optimization for Conjunctive Water Resources Management and Optimal Crop Planning in Kushabhadra-Bhargavi River Delta of Eastern India," IJERPH, MDPI, vol. 17(10), pages 1-20, May.
    14. Cao, Zhaodan & Zhu, Tingju & Cai, Ximing, 2023. "Hydro-agro-economic optimization for irrigated farming in an arid region: The Hetao Irrigation District, Inner Mongolia," Agricultural Water Management, Elsevier, vol. 277(C).
    15. Tang, Jiankai & Yang, Qiliang & Liang, Jiaping & Wang, Haidong & Yue, Xiulu, 2024. "Water management, planting slope indicators, and economic benefit analysis for Panax notoginseng production decision under shaded and rain-shelter cultivation: A three-year sloping fields experiment," Agricultural Water Management, Elsevier, vol. 291(C).
    16. Bonfante, A. & Monaco, E. & Manna, P. & De Mascellis, R. & Basile, A. & Buonanno, M. & Cantilena, G. & Esposito, A. & Tedeschi, A. & De Michele, C. & Belfiore, O. & Catapano, I. & Ludeno, G. & Salinas, 2019. "LCIS DSS—An irrigation supporting system for water use efficiency improvement in precision agriculture: A maize case study," Agricultural Systems, Elsevier, vol. 176(C).
    17. Chen, Shu & Shao, Dongguo & Tan, Xuezhi & Gu, Wenquan & Lei, Caixiu, 2017. "An interval multistage classified model for regional inter- and intra-seasonal water management under uncertain and nonstationary condition," Agricultural Water Management, Elsevier, vol. 191(C), pages 98-112.
    18. Jorge A. Garcia & Angelos Alamanos, 2022. "Integrated modelling approaches for sustainable agri-economic growth and environmental improvement: Examples from Canada, Greece, and Ireland," Papers 2208.09087, arXiv.org.
    19. Bhatta, Arun & Bigsby, Hugh R. & Cullen, Ross, 2011. "Alternative to Comprehensive Ecosystem Services Markets: The Contribution of Forest-Related Programs in New Zealand," 2011 Conference, August 25-26, 2011, Nelson, New Zealand 115350, New Zealand Agricultural and Resource Economics Society.
    20. Daniel Schatz & Rabih Bashroush, 0. "Economic valuation for information security investment: a systematic literature review," Information Systems Frontiers, Springer, vol. 0, pages 1-24.

    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:agisys:v:182:y:2020:i:c:s0308521x19315550. 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/agsy .

    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.