A sequential decision-making framework with uncertainty quantification for groundwater management

•Groundwater remediation planning and decision problem formulated as a partially observable Markov decision process (POMDP).•Comparison between POMDP and the conventional state-of-the-art optimization approaches, such as one-shot optimization and model predictive control (closed loop) optimization.•DESPOT, a state-of-the-art POMDP solver, outperforms optimization solution methods using PSO and hand-crafted heuristic solutions.•Optimizing the trade-off between information gathering and the performance of possible future scenarios via POMDP formulation.•Importance of belief updates, also known as inversion problems or history matching, in groundwater problems.