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Adjustable Robust Optimization for Multi-Period Water Allocation in Droughts Under Uncertainty

Author

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  • Yuhong Shuai

    (Sichuan University)

  • Liming Yao

    (Sichuan University
    Sichuan University)

Abstract

Optimal water resource allocation can go some way to overcoming water deficiencies; however, its achievement is complex due to conflicting hierarchies and uncertainties, such as water availability (WA) and water demand (WD). This study develops a robust water withdrawal scheme for drought regions that can balance the trade-offs between the sub-areas and water use participants, ensure sustainable regional system development, and guarantee robust solutions for future uncertainties. A bi-level affinely adjustable robust counterpart (AARC) programming framework was developed in which the regional authority as the leader allocates water to the sub-areas to maximize the intra- and intergenerational equity, and the sub-areas as the followers allocate water to their respective water departments to maximize their economic benefits and minimize water shortages. A case study from Neijiang, China, is given to illustrate the applicability and feasibility of this framework. The novelty of this study is to propose a sustainable bi-level AARC regional water allocation framework which integrates intra- and inter-generational equity of regional water use and priority rules reflected by goal preference programming between water departments under uncertainties of WA and WD simultaneously in water deficient regions.

Suggested Citation

  • Yuhong Shuai & Liming Yao, 2021. "Adjustable Robust Optimization for Multi-Period Water Allocation in Droughts Under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 4043-4065, September.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:12:d:10.1007_s11269-021-02929-w
    DOI: 10.1007/s11269-021-02929-w
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    1. Yan, Shiyu & Lv, Chengwei & Yao, Liming & Hu, Zhineng & Wang, Fengjuan, 2022. "Hybrid dynamic coal blending method to address multiple environmental objectives under a carbon emissions allocation mechanism," Energy, Elsevier, vol. 254(PB).

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