Balancing population demand and water stress in data centre siting under climate change: a spatial optimisation study across England

ABSTRACT Four-panel graphical summary arranged from left to right. The first panel shows rainfall, groundwater, river-flow reliability, population, and future scenarios as model inputs. The second panel shows a bi-objective optimisation balancing population coverage and water stress. The third panel shows maps of England indicating regional siting patterns. The final panel summarises the main population-water stress trade-off and the northward shift in preferred data centre locations. The rapid expansion of data centre infrastructure is increasing pressure on regional water resources, yet siting decisions remain largely driven by population and connectivity, with limited consideration of hydrological constraints. This paper develops a spatial optimisation framework that integrates a Water Resilience Index (WRI), combining rainfall, groundwater productivity, and river flow reliability, with a bi-objective integer linear programming (ILP) model that maximises population coverage while minimising aggregate water stress. The epsilon-constraint method is applied to generate complete Pareto frontiers across 295 local authority districts (LADs) in England under a baseline scenario (2026) and three future scenarios (2050–2100). Results reveal a persistent trade-off between service coverage and water sustainability, with optimal configurations systematically shifting away from the South-East towards northern regions as water stress intensifies. Highly populated areas, including London, are consistently excluded from balanced configurations across all scenarios. A sensitivity analysis of WRI component weighting confirms that this regional pattern is robust to the choice of weighting scheme. The framework provides a reproducible and transparent basis for incorporating hydrological constraints into digital infrastructure planning under climate change uncertainty.