How do data centres use and affect local water supplies?

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1. 1

   Data centre water consumption

   npj Clean Water (Mytton)Published Feb 15, 2021Checked Oct 13, 2026

   “To reliably support the online services used by these billions of users, data centres have been built around the world to provide the millions of servers they contain with access to power, cooling and internet connectivity. Whilst the energy consumption of these facilities regularly receives mainstream and academic coverage, analysis of their water consumption is scarce. Data centres consume water directly for cooling, in some cases 57% sourced from potable water, and indirectly through the water requirements of non-renewable electricity generation. Although in the USA, data centre water consumption (1.7 billion litres/day) is small compared to total water consumption (1218 billion litres/day), there are issues of transparency with less than a third of data centre operators measuring water consumption. This paper examines the water consumption of data centres, the measurement of that consumption, highlights the lack of data available to assess water efficiency, and discusses and where the industry is going in attempts to reduce future consumption.”

2. 2

   Artificial Intelligence and the Hidden Water Footprint of Data Centres: Cooling, Consumption and Environmental Sustainability

   Zenodo (CERN European Organization for Nuclear Research) (Thakur)Published Sep 30, 2026Checked Oct 13, 2026

   “This paper examines how AI data centres operate, why their cooling systems require water, and how the expansion of AI may affect freshwater resources. It adopts a secondary-research methodology based on peer-reviewed research, institutional reports, and publicly available environmental assessments. Particular attention is given to the distinction between water withdrawal and water consumption, because treating these measures as interchangeable can produce misleading conclusions. Existing research indicates that global AI-related water withdrawal could reach approximately 4.2–6.6 billion cubic metres annually by 2027 under the scenarios examined by Li et al. (2025). At the same time, technological developments such as direct-to-chip liquid cooling, closed-loop systems, dry cooling, improved data-centre siting, and water recycling provide opportunities to reduce freshwater dependence. The paper argues that the sustainability of AI cannot be assessed through energy and carbon metrics alone. Water availability must become an important consideration in the planning, operation, and governance of future AI infrastructure.”

3. 3

   Balancing Bits and Drops: Stress-Adjusted Water Management for Data Centers

   arXiv (Cornell University) (Talukder et al.)Published Jun 15, 2026Checked Oct 13, 2026

   “However, prior research has largely focused on reducing total water use, overlooking that the same unit of water can have drastically different environmental consequences depending on when and where it is consumed. In this paper, we introduce a stress-adjusted water framework that quantifies the true sustainability impact of data center water consumption by incorporating both spatial and temporal water stress. Using the AWARE-US model, we capture county-level monthly variations in water availability and extend this framework to account for the off-site water footprint of electricity generation. Based on this stress-aware accounting, we analyze stress-adjusted water-computing strategies spanning both the software and infrastructure layers. Specifically, we study workload scheduling policies that jointly optimize water and carbon efficiency, evaluate the potential of rainwater harvesting as a supplemental water source, and investigate the feasibility of dry cooling as a water-free alternative to evaporative cooling.”

4. 4

   Global data-water symbiosis reduces AI infrastructure's carbon and water footprint.

   Environmental science and ecotechnology (Wang et al.)Published Apr 26, 2026Checked Oct 13, 2026

   “The analysis reveals a strong global spatial co-occurrence between data centres and WWTPs, enabling optimized national-scale pairings in which treated effluent is used for data centre cooling and the return heat is recovered to support sludge drying and anaerobic digestion. This symbiotic approach reduces greenhouse gas emissions by approximately 84 million tonnes of CO2 equivalent annually, conserves approximately 1300 million m3 of freshwater, and provides net annual cost savings of approximately US$95.4 billion. The greatest mitigation and water-saving potential lies in the United States, Japan, China, the Netherlands, and the United Kingdom. These findings establish data-water symbiosis as a readily scalable infrastructure solution that decouples AI from its carbon and water footprints. WWTPs are poised to evolve from disposal facilities into critical energy-coupling hubs, enabling efficient thermal and water exchange across urban systems and accelerating progress towards multiple Sustainable Development Goals.”

5. 5

   Assessing Water Consumption and Cooling Efficiency Challenges Associated with Large-Scale Data Centre Growth and Operations

   International Journal of Science and Engineering Applications (Rawal)Published Oct 5, 2026Checked Oct 13, 2026

   “ntensive cooling systems.Although cooling is essential for maintaining reliable computing environments and preventing equipment failure, growing facility capacity can substantially increase water withdrawals and consumption, particularly in regions experiencing water scarcity and climate-related resource pressures.This study assesses water consumption and cooling-efficiency challenges associated with large-scale data centre growth and operations.It examines cooling-system design, climatic conditions, computing intensity, facility location, water usage effectiveness, and the relationship between water and energy efficiency.The analysis evaluates conventional cooling towers, air cooling, liquid cooling, immersion technologies, recycled-water utilization, and closed-loop systems as alternative approaches for reducing freshwater dependence.Particular attention is given to balancing thermal performance, electricity consumption, operational reliability, and regional water availability.The study develops a sustainability-oriented perspective for improving cooling efficiency while minimizing water-related environmental impacts throughout expanding data centre infrastructure and operations.”

6. 6

   Governing AI Data Center Growth in Water-Stressed Regions

   Advances in computational intelligence and robotics book series (Khaldy et al.)Published Jun 29, 2026Checked Oct 13, 2026

   “AI data centers are becoming critical infrastructure, but their growth is also a water-governance issue. Cooling systems can raise local freshwater demand directly, while electricity procurement adds indirect water use across power systems. In water-stressed regions, siting decisions affect not only land and grid capacity, but also basin resilience, transparency, and justice. This chapter develops a governance framework for AI data center growth that combines hydrological screening, public disclosure, and water-justice safeguards. It argues that responsible expansion requires place-based regulation that evaluates cumulative withdrawals, drought sensitivity, emergency curtailment, community participation, and enforceable reporting. Drawing on research on data center sustainability, water disclosure, planning, and environmental justice, the chapter proposes policy instruments for governments, utilities, and operators seeking water-resilient digital infrastructure.”

7. 7

   The island where locals say data centres are taking their water

   BBC NewsPublished Oct 12, 2026Checked Oct 13, 2026

   “"Not a single drop has come through our taps for the last three months," a local tells the BBC.”