Adaptive, multiobjective optimal sequencing approach for urban water supply augmentation under deep uncertainty

Abstract

Optimal long-term sequencing and scheduling play an important role in many water resources problems. The optimal sequencing of urban water supply augmentation options is one example of this. In this paper, an adaptive, multiobjective optimal sequencing approach for urban water supply augmentation under deep uncertainty is introduced. As part of the approach, optimal long-term sequence plans are updated at regular intervals and trade-offs between the robustness and flexibility of the solutions that have to be fixed at the current time and objectives over the entire planning horizon are considered when selecting the most appropriate course of action. The approach is demonstrated for the sequencing of urban water supply augmentation options for the southern Adelaide water supply system for two assumed future realities. The results demonstrate the utility of the proposed approach, as it is able to identify optimal sequences that perform better than those obtained using static approaches.