Skip to main content

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

Al-Maktoumi, A., Rajabi, M.M., Zekri, S., Triki, C. (2021) A Probabilistic Multiperiod Simulation–Optimization Approach for Dynamic Coastal Aquifer Management. Water Resources Management, 35 (11). pp. 3447-3462. ISSN 0920-4741. (doi:10.1007/s11269-021-02828-0) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:91477)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1007/s11269-021-02828-0

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.

Item Type: Article
DOI/Identification number: 10.1007/s11269-021-02828-0
Uncontrolled keywords: Aquifers; Groundwater resources; Stochastic systems; Water management, Coastal aquifer managements; Computational challenges; Groundwater abstraction; Groundwater management; Groundwater management plan; Optimization approach; Polynomial chaos expansion; Stochastic dynamic programming, Dynamic programming, coastal aquifer; computer simulation; groundwater abstraction; groundwater resource; numerical model; optimization; probability; recharge; stochasticity; uncertainty analysis; water management, Oman
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Chefi Triki
Date Deposited: 29 Nov 2021 12:14 UTC
Last Modified: 30 Nov 2021 14:21 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/91477 (The current URI for this page, for reference purposes)
Triki, C.: https://orcid.org/0000-0002-8750-2470
  • Depositors only (login required):