{"id":81192,"date":"2026-08-10T18:27:51","date_gmt":"2026-08-10T12:57:51","guid":{"rendered":"https:\/\/www.nextias.com\/ca\/?p=81192"},"modified":"2026-08-10T18:30:05","modified_gmt":"2026-08-10T13:00:05","slug":"ai-data-centres-water-footprint","status":"publish","type":"post","link":"https:\/\/www.nextias.com\/ca\/current-affairs\/10-08-2026\/ai-data-centres-water-footprint","title":{"rendered":"AI, Data Centres and India\u2019s Emerging Water Footprint"},"content":{"rendered":"\n<p><strong>Syllabus: GS3\/Science &amp; Technology<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Context<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The rapid expansion of AI and data centres has <a href=\"https:\/\/www.nextias.com\/ca\/editorial-analysis\/21-02-2026\/india-ai-data-centre-push\"><strong>highlighted their hidden water footprint<\/strong><\/a><strong>,<\/strong> raising concerns over groundwater depletion, cooling requirements and sustainability in water-stressed regions.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Emerging Water Footprint of AI<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Artificial Intelligence (AI) is often discussed in terms of computing power and electricity consumption, but <strong>water is an equally important resource for data-centre operations<\/strong>, particularly for cooling high-density computing systems.<\/li>\n\n\n\n<li>The University of California has estimated that a typical ChatGPT conversation of around 20\u201350 exchanges can have a water footprint of up to <strong>about 0.5 litre<\/strong>, depending on the location, cooling technology and electricity mix.\n<ul class=\"wp-block-list\">\n<li>It illustrates how seemingly intangible digital services have a physical environmental footprint.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>According to a <strong>UN assessment<\/strong>, data centres could have a <strong>water footprint of around 4.5 trillion litres in 2025<\/strong>, potentially rising to <strong>9.3 trillion litres by 2030<\/strong>.\n<ul class=\"wp-block-list\">\n<li>It arises both from direct cooling requirements and indirectly through water used in electricity generation.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>India\u2019s Data-Centre Expansion<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>India is emerging as a major global data-centre hub owing to rapid digitalisation, cloud computing, AI adoption and increasing data generation.\u00a0<\/li>\n\n\n\n<li>Data-centre capacity reportedly increased from around <strong>375 MW in 2020 to nearly 1,500 MW in 2025<\/strong>, with projections of <strong>13.56 GW by 2031\u201332<\/strong>.\n<ul class=\"wp-block-list\">\n<li><strong>Andhra Pradesh\u2019s Data Centre Policy 4.0<\/strong>, for instance, provides incentives such as GST reimbursement and stamp-duty exemptions.<\/li>\n\n\n\n<li>Uttar Pradesh\u2019s 2026 policy targets more than <strong>2 GW of additional capacity<\/strong>.<\/li>\n\n\n\n<li>Gujarat\u2019s 2026\u201329 policy aims at <strong>7.5 GW<\/strong> and investments of around <strong>\u20b96 lakh crore<\/strong>.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Key Issues &amp; Concerns<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Groundwater stress: <\/strong>The <strong>Central Ground Water Board (CGWB)\u2019s 2024 assessment<\/strong> puts India\u2019s stage of groundwater extraction at <strong>60.47%<\/strong>, with 11.1% of assessment units classified as over-exploited.\n<ul class=\"wp-block-list\">\n<li>The challenge becomes sharper when data centres are concentrated in already water-stressed urban clusters.<\/li>\n\n\n\n<li><strong>For Example:<\/strong>\n<ul class=\"wp-block-list\">\n<li>Gautam Buddha Nagar has numerous existing and upcoming data centres, while its groundwater extraction level has been assessed at <strong>104.79%<\/strong>.<\/li>\n\n\n\n<li>Hyderabad is also classified as over-exploited. Visakhapatnam, despite Andhra Pradesh\u2019s relatively comfortable state-level groundwater position, faces local resource constraints.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Lack of transparency: <\/strong>Many data centres do not publicly disclose their <strong>monthly or peak water consumption, water sources or proportion of potable, groundwater and reclaimed water<\/strong> used.\n<ul class=\"wp-block-list\">\n<li>It makes meaningful assessment of their local environmental impact difficult.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Water Energy Nexus: <\/strong>Data centres are highly electricity-intensive. Electricity generation itself can have a water footprint, creating an interconnected <strong>water-energy challenge<\/strong>.\n<ul class=\"wp-block-list\">\n<li>Excessive dependence on water-intensive cooling can also intensify competition between industrial and domestic requirements.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Coastal risks: <\/strong>Seawater cooling can reduce dependence on freshwater. However, the discharge of concentrated <strong>brine<\/strong> can affect marine ecosystems if inadequately managed.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Efforts &amp; Initiatives<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Andhra Pradesh Data Centre Policy 4.0<\/strong> provides fiscal and energy-related incentives for large data-centre projects.<\/li>\n\n\n\n<li><strong>UP Data Centre Policy, 2026<\/strong> seeks to expand capacity by over 2 GW.<\/li>\n\n\n\n<li><strong>Gujarat Data Centre Policy, 2026\u201329<\/strong> targets 7.5 GW of capacity.<\/li>\n\n\n\n<li>Companies are exploring <strong>seawater cooling<\/strong>, as demonstrated by Google\u2019s data centre in Finland.<\/li>\n\n\n\n<li>Greater adoption of <strong>reclaimed wastewater, closed-loop cooling and energy-efficient cooling technologies<\/strong> can reduce freshwater dependence.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Way Forward<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>India needs to pursue <strong>\u2018digital growth with water security\u2019<\/strong> rather than treating water availability as an externality.<\/li>\n\n\n\n<li><strong>Mandatory disclosure:<\/strong> Data centres should report monthly and peak water consumption, source-wise use and water intensity per unit of computing.<\/li>\n\n\n\n<li><strong>Water-stress-based regulation:<\/strong> New projects in over-exploited or stressed areas should face stricter environmental and groundwater permissions.<\/li>\n\n\n\n<li><strong>Prioritise non-potable water:<\/strong> Mandate greater use of treated wastewater and reclaimed water for cooling wherever technically feasible.<\/li>\n\n\n\n<li><strong>Promote water-efficient cooling:<\/strong> Encourage closed-loop, liquid, dry and hybrid cooling technologies according to local climatic conditions.<\/li>\n\n\n\n<li><strong>Integrated planning:<\/strong> Data-centre approvals should consider the combined <strong>water-energy-land and ecological carrying capacity<\/strong> of the region.<\/li>\n\n\n\n<li><strong>Responsible coastal cooling:<\/strong> Seawater systems should incorporate stringent brine-treatment and marine-impact monitoring.<\/li>\n<\/ul>\n\n\n\n<p><a href=\"https:\/\/www.thehindu.com\/business\/Economy\/hidden-environmental-cost-of-powering-growing-digital-and-ai-world\/article71322001.ece\" target=\"_blank\" rel=\"noopener\">Source: TH<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p><strong> Context <\/strong><\/p>\n<li class=\"ms-5\"> The rapid expansion of AI and data centres has highlighted their hidden water footprint, raising concerns over groundwater depletion, cooling requirements and sustainability in water-stressed regions. <\/li>\n<p><\/p>\n<p><strong> Emerging Water Footprint of AI <\/strong><\/p>\n<li class=\"ms-5\"> Artificial Intelligence (AI) is often discussed in terms of computing power and electricity consumption, but water is an equally important resource for data-centre operations, particularly for cooling high-density computing systems. <\/li>\n<li class=\"ms-5\"> The University of California has estimated that a typical ChatGPT conversation of around 20\u201350 exchanges can have a water footprint of up to about 0.5 litre, depending on the location, cooling technology and electricity mix. <\/li>\n<p><a href=\" https:\/\/www.nextias.com\/ca\/current-affairs\/10-08-2026\/ai-data-centres-water-footprint \" class=\"btn btn-primary btn-sm float-end\">Read More<\/a><\/p>\n","protected":false},"author":15,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[21],"tags":[],"class_list":["post-81192","post","type-post","status-publish","format-standard","hentry","category-current-affairs"],"acf":[],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts\/81192","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/users\/15"}],"replies":[{"embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/comments?post=81192"}],"version-history":[{"count":2,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts\/81192\/revisions"}],"predecessor-version":[{"id":81194,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts\/81192\/revisions\/81194"}],"wp:attachment":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/media?parent=81192"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/categories?post=81192"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/tags?post=81192"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}