Future-proofing urban water–energy resilience: An integrated system dynamics, optimization, and game-theoretic framework

Managing the Water-Energy Nexus (WEN) has emerged as a critical global challenge for countries pursuing net-zero emissions and the Sustainable Development Goals (SDGs). Like many other highly urbanized cities, Singapore faces this challenge acutely due to its land constraints, energy-intensive water infrastructure, and competing demands for renewable energy deployment. Previous studies have often examined these sectors in isolation, overlooking the dynamic feedback loops between energy-intensive water infrastructure and the land requirements of solar deployment. This study addresses this gap by developing a novel integrated decision-support framework that combines System Dynamics (SD) with a hybrid Multi-Objective Genetic Algorithm (MOGA), the Goal Attainment Method (GAM) and Cooperative Game Theory. The framework co-optimizes three conflicting objectives, namely system costs, water security, and reliance on fossil fuels, over a long-term planning horizon from 2025 to 2065. Three socio-economic scenarios are considered to account for future uncertainties. Results show that reactive planning leads to severe water deficits exceeding −660 million cubic meters by 2065. In contrast, the optimized pathway identifies a critical need for a synchronized surge in infrastructure commissioning between 2051 and 2060 to buffer the supply shock associated with the 2061 expiration of the water agreement. Regarding energy transition, solar photovoltaic (PV) capacity could peak at approximately 7020 MW-peak under the optimistic scenario. However, due to demand growth, solar energy's contribution to total electricity demand peaks at only 13.3% in the pessimistic scenario before declining as panels are decommissioned. The game theory analysis identifies a robust compromise solution that accepts a marginally higher economic cost to ensure water security remains above critical thresholds. This study offers an exploratory decision-support framework to assist policymakers in evaluating the synchronization of water and energy infrastructure investments under various socio-economic assumptions.