Proactive planning for water distribution system rehabilitation and expansion under long-term uncertainty

• Proactive approach developed to determine optimal rehabilitation timing and actions • Proactive approach achieves capital savings by postponing unnecessary actions • Timely rehabilitation enables water distribution systems sustain long-term reliability • Proactive approach minimises construction-related disruptions to the system • The framework enables informed decision-making based on subjective risk perception Long-term planning of water distribution system (WDS) rehabilitation is challenged by multiple sources of long-term uncertainty, under which the deterioration in system performance continues to evolve over time. Traditional rehabilitation approach typically assumes pre-defined intervention timing, which limits the flexibility in the rehabilitation strategy. This may lead to inefficient decisions when future system conditions deviate from expectations, thus reducing the hydraulic reliability of the system. To address this, a proactive planning framework has been developed, which consists of two components: 1) identifying optimal rehabilitation timing through system performance evaluation and 2) determining optimal rehabilitation actions through optimisation. A real-world case study has been used to evaluate the effectiveness of the proactive planning approach in comparison with the traditional approach. Results show that, by allowing rehabilitation actions to be timed in response to evolving system performance, construction-related disruptions can be minimised while the system reliability is effectively maintained. In addition, compared to the traditional approach, the proactive planning approach leads to more flexible and cost-effective rehabilitation plans, achieving substantial savings, especially in capital infrastructure investment. This study highlights the importance of timely rehabilitation in enabling WDSs to adapt to uncertain future conditions, ensuring long-term reliability and sustainability under uncertainty.