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Inclusion of Ecological Water Requirements in Optimization of Water Resource Allocation Under Changing Climatic Conditions

Author

Listed:
  • Wencong Yue

    (Research Center for Eco-Environmental Engineering, Dongguan University of Technology)

  • Zhongqi Liu

    (Research Center for Eco-Environmental Engineering, Dongguan University of Technology)

  • Meirong Su

    (Research Center for Eco-Environmental Engineering, Dongguan University of Technology)

  • Meng Xu

    (Zhejiang University of Finance & Economics)

  • Qiangqiang Rong

    (Research Center for Eco-Environmental Engineering, Dongguan University of Technology)

  • Chao Xu

    (Research Center for Eco-Environmental Engineering, Dongguan University of Technology)

  • Zhenkun Tan

    (Research Center for Eco-Environmental Engineering, Dongguan University of Technology)

  • Xuming Jiang

    (Research Center for Eco-Environmental Engineering, Dongguan University of Technology)

  • Zhixin Su

    (Research Center for Eco-Environmental Engineering, Dongguan University of Technology)

  • Yanpeng Cai

    (Guangdong University of Technology
    Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou))

Abstract

Meeting ecological water requirements (EWRs) is important for maintaining watershed system stability in many arid and semi-arid areas. Rainfall–runoff relationships under changing climate conditions could have many adverse effects on EWRs. The inherent uncertainties in water resource management and potential variations in EWRs should be considered to obtain suitable water allocation strategies under climate change. In this study, an integrated approach was proposed through incorporation of copula functions and a Markov Chain Monte Carlo (MCMC) simulation into a chance-constrained programming (CCP) model. The proposed approach had several advantages for water resource allocation under variable climatic conditions with respect to the following: (a) tackling correlated features of rainfall and watershed inflow under climate change based on copula–MCMC simulations, (b) obtaining runoff distributions using the copula sampling method under multiple climate change scenarios, (c) analyzing fluctuations in EWRs based on variable monthly flows and diverse runoff distributions, and (d) obtaining desired water allocation strategies through the developed CCP model with consideration of EWRs and water shortage risk. Application of the developed method to water resource management in the city of Dalian (China) indicated that the EWRs in the watersheds of Dalian would exhibit large variations under changing climatic conditions. Moreover, in comparison with the supply in 2025, an increase in water supply transferred from the Dahuofang Reservoir (Hun River) would be 6942–33,772, 6942–25,472, and 2849–14,259 Mt with risk tolerance levels of 20%, 50%, and 80%, respectively.

Suggested Citation

  • Wencong Yue & Zhongqi Liu & Meirong Su & Meng Xu & Qiangqiang Rong & Chao Xu & Zhenkun Tan & Xuming Jiang & Zhixin Su & Yanpeng Cai, 2022. "Inclusion of Ecological Water Requirements in Optimization of Water Resource Allocation Under Changing Climatic Conditions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 551-570, January.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:2:d:10.1007_s11269-021-03039-3
    DOI: 10.1007/s11269-021-03039-3
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    References listed on IDEAS

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    1. Nguyen-Huy, Thong & Deo, Ravinesh C. & An-Vo, Duc-Anh & Mushtaq, Shahbaz & Khan, Shahjahan, 2017. "Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones," Agricultural Water Management, Elsevier, vol. 191(C), pages 153-172.
    2. Wang, S. & Huang, G.H., 2014. "An integrated approach for water resources decision making under interactive and compound uncertainties," Omega, Elsevier, vol. 44(C), pages 32-40.
    3. L. Vergni & F. Todisco & F. Mannocchi, 2015. "Erratum to: Analysis of agricultural drought characteristics through a two-dimensional copula," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(11), pages 4203-4204, September.
    4. Dong-Dong Zhang & Deng-Hua Yan & Fan Lu & Yi-Cheng Wang & Jing Feng, 2015. "Copula-based risk assessment of drought in Yunnan province, China," 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. 75(3), pages 2199-2220, February.
    5. Yu, L. & Li, Y.P. & Huang, G.H. & Fan, Y.R. & Nie, S., 2018. "A copula-based flexible-stochastic programming method for planning regional energy system under multiple uncertainties: A case study of the urban agglomeration of Beijing and Tianjin," Applied Energy, Elsevier, vol. 210(C), pages 60-74.
    6. Gaivoronski, Alexei & Sechi, Giovanni M. & Zuddas, Paola, 2012. "Cost/risk balanced management of scarce resources using stochastic programming," European Journal of Operational Research, Elsevier, vol. 216(1), pages 214-224.
    7. Ali Torabi Haghighi & Nasim Fazel & Ali Akbar Hekmatzadeh & Björn Klöve, 2018. "Analysis of Effective Environmental Flow Release Strategies for Lake Urmia Restoration," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(11), pages 3595-3609, September.
    8. De Liu & Heping Zuo, 2012. "Statistical downscaling of daily climate variables for climate change impact assessment over New South Wales, Australia," Climatic Change, Springer, vol. 115(3), pages 629-666, December.
    9. Wu, C.B. & Huang, G.H. & Li, W. & Xie, Y.L. & Xu, Y., 2015. "Multistage stochastic inexact chance-constraint programming for an integrated biomass-municipal solid waste power supply management under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1244-1254.
    10. Chen, Shu & Xu, Jijun & Li, Qingqing & Tan, Xuezhi & Nong, Xizhi, 2019. "A copula-based interval-bistochastic programming method for regional water allocation under uncertainty," Agricultural Water Management, Elsevier, vol. 217(C), pages 154-164.
    11. A. E. Brookfield & C. Gnau, 2016. "Optimizing Water Management for Irrigation Under Climate Uncertainty: Evaluating Operational and Structural Alternatives in the Lower Republican River Basin, Kansas, USA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 607-622, January.
    12. A. Brookfield & C. Gnau, 2016. "Optimizing Water Management for Irrigation Under Climate Uncertainty: Evaluating Operational and Structural Alternatives in the Lower Republican River Basin, Kansas, USA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 607-622, January.
    13. Xiao-jun Wang & Jian-yun Zhang & Shamsuddin Shahid & Shou-hai Bi & Amgad Elmahdi & Chuan-hua Liao & You-de Li, 2018. "Forecasting industrial water demand in Huaihe River Basin due to environmental changes," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(4), pages 469-483, April.
    14. Hadi Tarebari & Amir Hossein Javid & Seyyed Ahmad Mirbagheri & Hedayat Fahmi, 2018. "Multi-Objective Surface Water Resource Management Considering Conflict Resolution and Utility Function Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4487-4509, November.
    15. L. Vergni & F. Todisco & F. Mannocchi, 2015. "Analysis of agricultural drought characteristics through a two-dimensional copula," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2819-2835, June.
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    Cited by:

    1. Haipeng Xu & Dequan Zhang & Yao Wu & Peng Qi & Xiaofeng Wang, 2024. "Suitable Ecological Water Demand for Wetlands Restored to Different Historical Periods in a Latitude area and their Response to Changing Environments," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(14), pages 5683-5700, November.

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