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.

综合模拟优化 (CSO) 方案在解决不同地下水管理问题的文献中很常见，而 CSO 在沿海含水层管理文献中尤其成熟。然而，除了少数例外，几乎所有以前的研究都采用 CSO 方法来推导出在整个管理期间保持不变的静态地下水管理计划，因此忽略了动态策略可能产生的积极影响。动态策略涉及将规划时间间隔划分为几个子间隔或时期，并在每个时期根据地下水系统及其相关不确定性的最新知识采用修订的决策。问题结构和计算挑战似乎是阻碍在地下水应用中广泛实施动态策略的主要因素。本研究的目的是通过引入一种用于动态地下水管理的新型概率多周期 CSO 方法来应对这些挑战。这包括重新制定地下水管理问题，使其适用于多周期 CSO 方法，以及随后采用基于多项式混沌扩展的随机动态规划以获得最佳动态策略。考虑到自然补给不确定性的影响，所提出的方法用于为阿曼的沿海含水层储存和回收设施提供可持续的解决方案。