Future supply, demand, and vulnerability of domestic water supply systems in Asian mega cities

Rapid urbanization and income growth are reshaping domestic water demand across Asian megacities. Accordingly, we developed an integrated system dynamics model at the city scale to reconstruct the domestic water demand and supply for 42 megacities from 2015 to 2035. The cities were clustered into five archetypes based on climatic conditions, technological advancement (TA), wastewater reuse (WR), and economic growth trajectories, and uncertainty was quantified using a Monte Carlo (MC) ensemble. We summarized this uncertainty by reporting the 5th-95th percentile range of key risk metrics for each city and synthesized four indicators, namely shortage depth, frequency, probability, and urgency, into a composite vulnerability index (CVI). Our results revealed the concentration of demand growth in South Asia and the Pearl River region, whereas East Asian megacities exhibited flat or declining trajectories. The MC analysis indicated a near-universal risk, with the median probability of at least one shortfall defined as a water supply-to-demand ratio (WSDR) <1 between 2015 and 2035 at 1.00 for every archetype. Furthermore, archetypes 1, 2, 4, and 5 were projected to remain below sufficiency for nearly the entire period, whereas archetype 3 would sustain sufficiency for a median of 16 years. Minimum WSDR medians ranged from 0.44 (in archetype 2) to 0.83-0.85 in buffered cities like Hong Kong and Shanghai. CVI spanned 27.6-80.0 across the cities, with Chennai, Shenzhen, Surat, Bengaluru, and Kolkata ranking highest, and Chongqing, Shanghai, Hyderabad, Hong Kong, Nagoya, and Tokyo ranking lowest. The archetype-level CVI was highest for archetypes 2 and 1 and lowest for archetype 3. Our findings highlight that large-scale TA consistently improves WSDR, whereas the effects of WR remain heterogeneous and context-dependent. We also confirmed climate variability to be a persistent stressor. Overall, this framework offers comparable, uncertainty-aware diagnostics to prioritize efficiency, reuse integration, and supply augmentation programs across diverse urban contexts.