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A Probabilistic Multiperiod Simulation–Optimization Approach for Dynamic Coastal Aquifer Management

Abstract

Combined simulation–optimization (CSO) schemes are common in the literature to solve different groundwater management problems, and CSO is particularly well-established in the coastal aquifer management literature. However, with a few exceptions, nearly all previous studies have employed the CSO approach to derive static groundwater management plans that remain unchanged during the entire management period, consequently overlooking the possible positive impacts of dynamic strategies. Dynamic strategies involve division of the planning time interval into several subintervals or periods, and adoption of revised decisions during each period based on the most recent knowledge of the groundwater system and its associated uncertainties. Problem structuring and computational challenges seem to be the main factors preventing the widespread implementation of dynamic strategies in groundwater applications. The objective of this study is to address these challenges by introducing a novel probabilistic Multiperiod CSO approach for dynamic groundwater management. This includes reformulation of the groundwater management problem so that it can be adapted to the multiperiod CSO approach, and subsequent employment of polynomial chaos expansion-based stochastic dynamic programming to obtain optimal dynamic strategies. The proposed approach is employed to provide sustainable solutions for a coastal aquifer storage and recovery facility in Oman, considering the effect of natural recharge uncertainty. It is revealed that the proposed dynamic approach results in an improved performance by taking advantage of system variations, allowing for increased groundwater abstraction, injection and hence monetary benefit compared to the commonly used static optimization approach.

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Data Availability

Available from the corresponding author upon request.

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Acknowledgment

The authors would like to acknowledge the financial support of Sultan Qaboos University through the grant EG/DVC/WRC/14/2 and to DR/RG/17. Authors also appreciate the support of the Public Authority of Water, and the Ministry of Regional Municipalities and Water Resources in Oman for providing data and information for the study. The authors wish to thank Editor-in-Chief, Professor George Tsakiris, Associate Editor and two anonymous reviewers for their valuable comments which helped to improve the final manuscript.

Funding

See the Acknowledgments section.

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Authors

Contributions

Ali Al-Maktoumi: Funding, Data Curation, Groundwater Modeling, Review & Editing; Mohammad Mahdi Rajabi: Methodology, Groundwater Modeling, Code Development, Data Analysis, Original Draft Preparation; Slim Zekri: Conceptualization, Optimization and Analysis, Review & Editing; Chefi Triki: Conceptualization, Optimization and Analysis; Review & Editing.

Corresponding author

Correspondence to Mohammad Mahdi Rajabi.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Al-Maktoumi, A., Rajabi, M.M., Zekri, S. et al. A Probabilistic Multiperiod Simulation–Optimization Approach for Dynamic Coastal Aquifer Management. Water Resour Manage 35, 3447–3462 (2021). https://doi.org/10.1007/s11269-021-02828-0

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Keywords

  • Combined simulation–optimization
  • Multiperiod management
  • Stochastic dynamic programming
  • Polynomial chaos expansion
  • Coastal aquifer