Artificial Intelligence: A Great Solution or A Severe Problem for A Thirsty World?
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References
[1] European Commission. (2025, June 4). European water resilience strategy. https://environment.ec.europa.eu/publications/european-water-resilience-strategy_en
[2] Liang, Y., Ding, F., Liu, L., Yin, F., Hao, M., Kang, T., Zhao, C., Wang, Z., & Jiang, D. (2025). Monitoring water quality parameters in urban rivers using multi-source data and machine learning approach. Journal of Hydrology, 648, Article 132394.
[3] Ma, X., Weng, S., Zhao, X., Li, J., & Haider, S. (2024). Investigating the impact of artificial intelligence development on water pollution in China. Gondwana Research, 132, 182–192.
[4] QazInform. (n.d.). China managing its water quality with AI. https://qazinform.com/news/china-managing-its-water-quality-with-ai-f19688
[5] Singh, S., & Goyal, M. K. (2025). A review of India's water policy and implementation toward a sustainable future. Journal of Water and Climate Change, 16(2), 493–510. https://doi.org/10.2166/wcc.2025.560
[6] Center for Strategic and International Studies. (n.d.). How artificial intelligence can help solve India’s water utility problems. https://www.csis.org/analysis/how-artificial-intelligence-can-help-solve-indias-water-utility-problems
[7] United Nations Educational, Scientific and Cultural Organization. (2026). UNESCO hands over equipment to strengthen early warning systems in Central Asia at RES-2026. https://www.unesco.org/en/articles/unesco-hands-over-equipment-strengthen-early-warning-systems-central-asia-res-2026
[8] United Nations Sustainable Development Goals. (n.d.). Tajikistan manages water with AI innovation. https://unsdg.un.org/latest/stories/tajikistan-manages-water-ai-innovation
[9] Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., & Madani, K. (2026). Environmental cost of AI's energy use: Carbon, water and land footprints. United Nations University Institute for Water, Environment and Health. https://doi.org/10.53328/INR26RMA002
[10] Al Kez, D., Foley, A. M., Hasan Wong, F. W. B. M., Dolfi, A., & Srinivasan, G. (2025). AI-driven cooling technologies for high-performance data centres: State-of-the-art review and future directions. Sustainable Energy Technologies and Assessments, 82, Article 104511.
[11] Qin, Y., Wang, Y., Li, S., Deng, H., Wanders, N., Bosmans, J., Huang, L., Hong, C., Byers, E., Gingerich, D., Bielicki, J. M., & He, G. (2023). Global assessment of the carbon–water tradeoff of dry cooling for thermal power generation. Nature Water, 1, 682–693. https://doi.org/10.1038/s44221-023-00120-6
[12] International Energy Agency. (2025). Energy and AI. https://iea.blob.core.windows.net/assets/de9dea13-b07d-42c5-a398-d1b3ae17d866/EnergyandAI.pdf
[13] Mytton, D. (2021). Data centre water consumption. npj Clean Water, 4, Article 11. https://doi.org/10.1038/s44221-021-00011-8
[14] Barringer, F. (2025). Thirsty for power and water. AI crunching data centers sprout across the West. Bill Lane Center for the American West, Stanford University. https://andthewest.stanford.edu/2025/thirsty-for-power-and-water-ai-crunching-data-centers-sprout-across-the-west/
[15] Abdelmohsen, K., et al. (2025). Declining freshwater availability in the Colorado River basin threatens sustainability of its critical groundwater supplies. Geophysical Research Letters, 52, Article e2025GL115593. https://doi.org/10.1029/2025GL115593
[16] Privette, A. P., Barros, A., & Cai, X. (2026). Data centers water footprint: The need for more transparency. AGU Advances, 7, Article e2025AV002140. https://doi.org/10.1029/2025AV002140
[17] Sanders, M. (2026, March 20). World water day and the hidden water footprint of AI. Forbes. https://www.forbes.com/sites/monicasanders/2026/03/20/world-water-day-and-the-hidden-water-footprint-of-ai/
[18] Lawrence Berkeley National Laboratory. (2024). 2024 LBNL data center energy usage report. https://eta.lbl.gov/publications/2024-lbnl-data-center-energy-usage-report
[19] Xiao, T., Nerini, F. F., Matthews, H. D., Tavoni, M., & You, F. (2025). Environmental impact and net-zero pathways for sustainable artificial intelligence servers in the USA. Nature Sustainability, 8, 1541–1553. https://doi.org/10.1038/s41893-025-01681-y
[20] Díaz-Marín, C. D., & Berquist, Z. J. (2025). Flipping the switch: Carbon-negative and water-positive data centers through waste heat utilization. Energy & Environmental Science, 18, 8403. https://doi.org/10.1039/d5ee02676h
[21] The Economist. (2026, May 21). Elon Musk is going all-in on an unproven technology. https://www.economist.com/briefing/2026/05/21/elon-musk-is-going-all-in-on-an-unproven-technology
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Copyright (c) 2026 Maria Giovanna Buonomenna, Aliaksei Patonia (Author)

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