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  • Imperial Valley’s 330 MW Lawsuit Shows Water Rights Can Gate AI-Era Capacity

    Imperial Valley’s 330 MW Lawsuit Shows Water Rights Can Gate AI-Era Capacity

    TL;DR · 30-second read

    The Short Version

    A company planning California’s largest data center, a huge building full of computers like the ones that run AI tools, was refused the water it needs to keep those machines cool. It is now suing the public agency that controls the local water.

    The water comes from the Colorado River. About 40 million people in seven states depend on that river, and drought has strained it. The company wants to take over water that farms use today.

    The court case could help decide whether water, not only electricity, limits where the AI boom can be built.

    BGR reported on August 12, 2026 that Imperial Valley Computer Manufacturing has sued the Imperial Irrigation District (IID), the public agency that delivers Colorado River water to California’s Imperial Valley. IID had denied the developer’s request to use the district’s water supply and wastewater to cool a planned 330-megawatt data center, which would be the largest in California. The facility is expected to require 287 million gallons of water.

    The developer plans to source that water by reallocating it from farmland. Its lawsuit argues there is “no rational basis” for IID to bar an industrial company from combining several fields into a single unit for water reallocation while allowing agricultural users to do the same.

    Executive Summary

    Most debate about where AI data centers can be built focuses on electricity: whether the grid can deliver hundreds of megawatts, and how fast. The Imperial Valley dispute puts a different constraint in front of a court. The developer’s cooling plan depends on moving existing farm water allocations to an industrial user, and the agency that controls those allocations has said no.

    The legal question is narrow, whether an industrial user may aggregate and transfer water the way farmers already can. The practical stakes are broad. If water rules can block a 330-megawatt project in one of the most water-contested basins in the country, developers eyeing arid regions will have to treat water rights as a gating item on par with a power connection, not as a permit to settle later.

    Sebastian Rucci, the figure leading the project, argues the data center would use about as much water as a 160-acre farm and would benefit the local economy. Critics counter that reallocating farm water puts rural communities at risk, and local residents broadly favor a moratorium on new data center construction.

    Why Water Rights, Not Just Megawatts, Gate This Project

    A data center’s electrical rating, here 330 megawatts, describes how much power its computers and support systems can draw. Nearly all of that electricity ends up as heat, which has to be removed continuously. Many large facilities do this with evaporative cooling, in which water is evaporated in cooling towers to carry heat away. That design is efficient on electricity but consumes water in proportion to the heat load, which is why a 330-megawatt campus arrives with a 287-million-gallon water requirement attached.

    In the Imperial Valley, that water has to come from somewhere already spoken for. IID delivers Colorado River water to the region, and the developer’s plan is to reallocate water currently tied to farmland. IID’s denial covered both its water supply and its wastewater, closing off reclaimed water as well as fresh. As things stand, the project’s cooling design cannot proceed on the terms the developer proposed, whatever its power situation. That is the mechanism the title points to: a local water agency’s allocation rules, not the grid, are the decision point currently holding up this capacity.

    The people affected extend beyond one developer. Anyone siting large facilities in the arid Southwest, where land and solar power are attractive, now has a live example of water access acting as a hard stop. Water agencies are affected too, since a ruling will signal how much discretion they have to treat industrial and agricultural transfers differently.

    The Legal Question: Can Industry Aggregate Water Like Farms Do?

    The lawsuit’s core argument is about equal treatment. According to the complaint as described, IID lets agricultural users combine multiple fields into a single unit for water reallocation but refused to let an industrial company do the same. The developer says there is “no rational basis” for the distinction.

    That phrasing echoes a well-established legal standard under which a government body’s line-drawing generally survives if any reasonable justification exists. It is typically a demanding standard for challengers. IID may point to its mandate to serve agriculture, drought conditions on the Colorado River, or the difference between water that stays in farming and water permanently moved to a new industrial use. The developer will argue that water is water and that the district cannot favor one class of user without a principled reason.

    Either outcome sets a marker. A win for the developer would suggest farm water allocations in the district can be assembled and redirected to data centers, which would change land and water economics in the valley. A win for IID would confirm that water agencies can effectively decide whether water-intensive data centers get built in their service areas.

    Testing the 160-Acre Farm Comparison

    Rucci’s claim that the facility would have as much impact as a 160-acre farm can be checked against the stated figure. Dividing 287 million gallons across 160 acres works out to roughly 1.8 million gallons per acre, or about 5.5 acre-feet, the unit water managers use, where one acre-foot covers an acre of land a foot deep. Whether that matches a typical Imperial Valley farm depends on the crop and on whether 287 million gallons is an annual figure, which has not been specified.

    The comparison also answers a different question from the one critics are asking. Their objection is less about the total volume than about where it comes from: water moved out of farming, in a region where agriculture sustains rural livelihoods, from a river that serves 40 million people across seven states. It also leaves open how much of the data center’s water would be consumed through evaporation versus returned to the system, a distinction that matters for downstream users.

    Local Opposition Is Part of the Siting Math

    Residents in the area generally favor a strict moratorium on new data center construction, according to the reporting, reflecting concerns about utility prices and water strain that have followed data center projects in other regions. Rucci has argued the project would bring economic benefits, but the specifics of jobs, tax revenue or community agreements have not been laid out.

    For the industry, the lesson is that community sentiment and water governance are converging into a single siting risk. A project that must win both a court case over water allocation and a skeptical local public faces a longer and less predictable path than one that secures water and community support before it announces its scale.

    Background

    The Imperial Valley sits in California’s southeastern desert and depends on Colorado River water delivered by the Imperial Irrigation District, much of it for farming. The Colorado River supplies roughly 40 million people across seven U.S. states and has faced years of drought, making any new large draw on it contentious.

    Data centers have become one of the fastest-growing sources of industrial demand for both electricity and water as companies build capacity for artificial intelligence. Their water use comes mainly from cooling, and communities in several regions have pushed back on new facilities over utility costs and water strain, making water sourcing an increasingly visible part of the siting process.

    Sources

    Source: The Largest Data Center In California Has Been Denied Water For Cooling — Now It’s Suing A Public Agency (BGR), on Imperial Valley Computer Manufacturing’s lawsuit against the Imperial Irrigation District over cooling water for a planned 330 MW data center.

  • Salem Data Center’s 3M-Gallon Hot-Day Peak Shows Why Annual Water Totals Mislead

    Salem Data Center’s 3M-Gallon Hot-Day Peak Shows Why Annual Water Totals Mislead

    TL;DR · 30-second read

    The Short Version

    A company wants to build a data center, a large building full of computers, in Salem, Oregon. On the hottest days, its design lets it use up to 3 million gallons of water, about four and a half Olympic swimming pools, mostly to keep those computers cool.

    Over a full year it expects to use far less, about 39 million gallons. The catch is timing: its thirstiest days are the same hot days when everyone else in town is also using the most water.

    Salem’s city council is now discussing whether to pause projects like this.

    A data center proposed for Salem, Oregon, is designed to use up to 3 million gallons of water a day on the city’s hottest days and roughly 39 million gallons over a full year, the Salem Reporter reported on August 5, 2026. The figures describe the first phase of a proposed multi-phase project from developer Verrus.

    The numbers arrive as local opposition grows. Residents holding signs against the project attended a Salem City Council meeting this summer, where the council heard public comment and discussed the process for a possible moratorium on the project.

    Executive Summary

    The two water figures attached to Salem’s proposed data center describe very different things. Roughly 39 million gallons a year works out to an average of about 107,000 gallons a day. The design peak of 3 million gallons on the hottest days is roughly 28 times that average. The annual number describes volume; the peak number describes how much capacity the city’s water system must be able to deliver on a single day.

    That distinction matters because water systems are sized, and water is rationed, around the highest-demand days of the year. A facility whose use spikes during heat waves asks for the most water precisely when residential and irrigation demand is also at its maximum and western Oregon is in its dry season.

    For the wider data center industry, Salem is a preview of the question operators will increasingly face: not how much water a campus uses in a year, but how much it needs on the worst day, and who gets priority when the two collide.

    The Number That Matters Is the Peak Day

    An annual figure of 39 million gallons sounds modest next to a city’s total water use, and that is the figure most likely to appear in a sustainability report. But the arithmetic behind the two disclosed numbers tells a different story. Spread evenly, 39 million gallons is about 107,000 gallons a day. The 3-million-gallon design peak is roughly 28 times that. Put another way, just 13 days at full peak would consume the entire annual total. The facility’s water demand is not a steady trickle; it is a low baseline with sharp spikes tied to temperature.

    Water utilities plan around those spikes. Treatment plants, pumps, pipes and storage reservoirs are built to meet the maximum-day demand, not the yearly average, because running short on one hot afternoon is the failure that matters. A large user whose demand concentrates in heat waves therefore consumes a disproportionate share of the system’s capacity, even if its annual share looks small. That is why the annual figure understates the strain, and why the peak figure is the one city engineers and councils need to evaluate.

    The people most affected are the ones already competing for water on those days: households watering lawns and gardens, farms irrigating crops, and the rivers that carry less water in late summer. A data center’s peak does not create that summer squeeze, but it lands directly on top of it.

    Why Cooling Demand Tracks the Thermometer

    Data centers turn nearly all the electricity they use into heat, and that heat has to go somewhere. One of the most energy-efficient ways to move it out is evaporation: warm water passes through cooling towers, some of it evaporates, and the evaporation carries heat away, much as sweat cools a person. The hotter and drier the outside air, the more water that approach consumes. A design that uses little water most of the year but spikes on hot days is the typical signature of cooling that leans on evaporation when outside air alone is not enough.

    The alternative, often described as closed-loop or dry cooling, recirculates the same water and rejects heat through fans and chillers, much like a car radiator. It uses far less water but more electricity, and its electricity demand also rises on hot days, when the regional power grid is under its own peak load. Neither choice is free. The design decision determines whether a facility leans on the water system or the power system during a heat wave, and on the hottest days both are stretched.

    A First Phase, and a Council Weighing a Pause

    The disclosed figures cover only the first phase of a multi-phase project. Whether later phases would add proportionally to peak water demand, use a different cooling design, or rely on another water source has a direct bearing on how the city should read the first-phase numbers. A peak figure that is manageable for one building could look different across a full campus.

    The council’s discussion of a possible moratorium reflects how quickly the conversation shifts once peak-day figures are public. Communities elsewhere have used tools short of an outright pause: caps on peak-day withdrawals, contracts requiring a facility to curtail water use during declared shortages, requirements to use recycled rather than drinking water, and on-site storage that fills during cool periods. Which of these, if any, are on the table in Salem is not yet clear, but they show that the peak problem has engineering and contractual answers, not only yes-or-no ones.

    Background

    Salem is Oregon’s capital, and Oregon has long been a data center destination, with large campuses in Hillsboro west of Portland and along the Columbia River in The Dalles and in Central Oregon at Prineville. Cool climates, available land and access to power have drawn operators, and water has become a recurring point of friction: in The Dalles, the scale of Google’s water use became public only after a public-records dispute.

    Across the industry, water disclosure has lagged behind energy disclosure. Operators often report annual totals or efficiency ratios in sustainability reports, but peak-day demand, the figure that determines how much capacity a municipal system must provide, is rarely published. As data center demand grows, local governments are increasingly asking for that number before approving new campuses.

    Sources

    Source: Data center designed to use up to 3 million gallons on Salem’s hottest days — Salem Reporter coverage of the proposed data center’s peak and annual water use.

  • Pentagon Offers AI Data Centers Land at 12 Bases; the Real Price Is Off-Grid Power

    Pentagon Offers AI Data Centers Land at 12 Bases; the Real Price Is Off-Grid Power

    TL;DR · 30-second read

    The Short Version

    The US military is inviting private companies to build giant computer warehouses for artificial intelligence on at least 12 of its bases, from Texas to Alaska. Two projects, each estimated at about $2 billion, have been tentatively awarded.

    The military pays nothing up front. In exchange for the land, it gets to use the computers. The catch is that each project must make its own electricity instead of plugging into local power lines, and must not drain local water. In effect, the builders are being asked to build their own power plant too.

    Some proposed sites sit half a mile from family homes, and Congress is still arguing over the rules.

    Military.com reported on July 27, 2026 that the Army and the Department of the Air Force have opened at least a dozen military installations to commercial data center developers over the past year and a half. Only two deals have been awarded, and both are conditional. In late March the Army selected Carlyle for roughly 1,384 acres at Fort Bliss, Texas. It selected CyrusOne, a data center operator jointly held by funds managed by KKR and BlackRock, for a roughly 1,201-acre parcel at Dugway Proving Ground, Utah. The Financial Times estimated each project at about $2 billion.

    The other sites are still solicitations. The Army is considering Fort Hood, Texas, and Fort Bragg, North Carolina. The Air Force has sought bids at Arnold, Edwards, Joint Base McGuire-Dix-Lakehurst, Davis-Monthan and Robins, and more recently at Joint Base Elmendorf-Richardson, Eielson Air Force Base and Clear Space Force Station in Alaska. Proposals must include net-zero water usage and a power plan that does not draw on the local electrical grid. Initial operating capability is projected for fiscal 2027 at Fort Bliss and fiscal 2029 at Dugway.

    Executive Summary

    The Pentagon is turning spare base land into a currency for AI computing. Under the Army’s Enhanced Use Lease program, private developers finance, build, operate and eventually decommission hyperscale data centers on military land. Hyperscale refers to the warehouse-sized campuses built for the largest cloud and AI workloads. In return the service gets access to computing power, at what the Army calls “no upfront cost to taxpayers.” Army Secretary Dan Driscoll has described Fort Bliss as “the first hyper-scale data center that the Pentagon has ever done.”

    The terms matter more than the land. Unlike commercial projects off base, these bids must bring a power plan that does not rely on the local grid and must achieve net-zero water use. For developers, that changes the job from building a data center to building a data center plus its own utility. For base commanders and the surrounding communities, siting and power have become part of the procurement itself.

    The program is also politically unsettled. A House defense bill provision would bar leases unless developers exclude certain components from China, Russia, Iran and North Korea, and the Army has objected that the rule would penalize building on federal land.

    The Land Is Free. The Power Plant Is Not.

    In the commercial market, the scarcest input for a large AI campus is usually a grid connection, not land. A grid connection is the utility’s commitment to deliver large, steady amounts of electricity, and it often comes only after a long wait in an interconnection queue, the line of projects waiting for approval to plug in. The Army and Air Force solicitations rule that path out. Proposals must include a power plan that does not draw on the local electrical grid, a requirement that does not apply to identical projects built off base.

    That changes what is actually being procured. The Army’s side of the bargain, land in exchange for computing access, is accurate in cash terms, but it moves the heaviest capital item onto the bidder. Whoever builds at Fort Bliss or Dugway is committing to finance and run generation as well as the data halls. The Army’s long-term vision, as described by Col. John Oliver, is a campus with a commercial side, a classified military data side and onsite power generation. The roughly $2 billion estimate for each project has not been broken down publicly, so nobody outside the negotiations can yet say how much of it is power plant and how much is computing.

    The rule is likely to favor sponsors with deep capital and power-development experience, such as a global investment firm like Carlyle or a KKR- and BlackRock-backed operator like CyrusOne, over developers whose model depends on buying utility power. It also changes the utility relationship. El Paso Electric attended the Army’s spring listening session at Fort Bliss, and the Army says excess power generated on base could potentially be sold back to civilian grids. A would-be large customer could become a supplier instead. For residents, the rule speaks directly to the concern behind a Virginia state-funded study, which found monthly household energy bills there could rise by $14 to $37 by 2040 as data centers grow.

    Water Is the Second Utility the Bidder Must Bring

    Data centers use water to cool their servers, and the net-zero water requirement is hardest to meet at the Army’s flagship site. Defense Department procurement documents reported by Data Center Dynamics rate the water risk for the El Paso area as “Extremely High.” One option under discussion is having Carlyle drill a new well to feed El Paso’s desalination plant and offset what the data center uses. Oliver was candid that this is unproven: “We don’t know if that’s an engineering solution that we can actually get to yet.”

    Water and power are linked. Cooling designs that use less water generally use more electricity. In a desert location, a strict water target therefore adds to the size of the on-site generation the developer must build and pay for. The two requirements compound rather than sit side by side.

    A Dozen Sites, Two Awards, Very Different Neighbors

    The sites vary widely. Dugway, where the military conducts its primary chemical and biological weapons testing, offers three parcels totaling about 3,466 acres, roughly an hour’s drive from the nearest community. Fort Hood has 207 acres on offer, and Fort Bliss has nearly seven times that. Contracting documents show a Fort Hood parcel within a half-mile of residential and commercial property, and several Fort Bragg locations within a mile of civilian areas and a half-mile of civilian housing. Smaller parcels close to homes leave less room for generation, and less buffer for its noise, than a remote range does.

    Opposition near homes is not a hypothetical risk. Data Center Watch counts nearly $156 billion in projects nationwide delayed or canceled after local opposition. The Army has built community engagement into the bid: developers must describe outreach plans and assess “any risks or opposition.” Brookings senior fellow Darrell M. West said communities that accept these facilities tend to be the ones told the details up front, including energy source, water use, cost and noise.

    Congress Is Still Writing the Rules

    Rep. Cory Mills secured a provision in the House fiscal 2027 defense authorization bill barring data center leases unless developers avoid certain printed circuit boards, advanced semiconductors and chipsets made in China, Russia, Iran or North Korea. The Army objected that it would create a “federal land penalty,” imposing rules on installations that would not apply to identical projects anywhere else. Rep. John Garamendi’s proposal to require evaluation of energy, water, noise, light and security effects before any deal was rejected by House Armed Services Republicans. A Senate amendment to pause leasing until the Pentagon finalizes a data center strategy was also defeated.

    Each condition adds to the same balance sheet. Free land has to pay for off-grid generation, net-zero water and possibly a restricted supply chain, and the Army’s own argument shows it knows the margin is not unlimited. Whether the economics still work at scale is the question the two conditional awards will answer first.

    Background

    AI workloads have pushed demand for hyperscale data centers faster than utilities can connect them, and local opposition has become a real constraint, with Data Center Watch counting nearly $156 billion in projects delayed or canceled. The Pentagon holds large tracts of underused land at remote and secure installations, and a Trump executive order directed agencies to open non-excess federal land to data center development. The Army’s Enhanced Use Lease program, with the U.S. Army Corps of Engineers handling lease negotiations and environmental review, is the vehicle.

    Carlyle is a global investment firm. CyrusOne is a data center operator jointly held by funds managed by KKR and BlackRock. Dugway Proving Ground in Utah is where the U.S. military conducts its primary chemical and biological weapons testing, and Fort Bliss in El Paso is home to the Army’s 1st Armored Division.

    Sources

    Source: Pentagon Plans AI Data Centers at Military Bases Across Multiple Branches (Military.com), on Army and Air Force plans to lease base land to commercial AI data center developers.

  • Infinium’s 1 MW in 250 Sq Ft Shows Waterless AI Cooling’s Real Test Is Heat Rejection

    Infinium’s 1 MW in 250 Sq Ft Shows Waterless AI Cooling’s Real Test Is Heat Rejection

    TL;DR · 30-second read

    The Short Version

    A Sacramento company best known for making clean fuel has launched a cooling system for the computer buildings behind artificial intelligence. Its selling point is that it uses no water.

    Instead of blowing cold air over computers, it sinks them in a liquid that does not conduct electricity. The company says one unit can handle up to a megawatt of computing, roughly the electricity several hundred homes use, in a space about the size of a large bedroom.

    The catch is that the heat still has to go somewhere, and the company has not said how the system copes on a hot day.

    Infinium, a Sacramento clean-fuel company, has unveiled the EdgeSites Vector ONE, a self-contained data center cooling system that uses no water, the Sacramento Business Journal reported on July 27, 2026. The system submerges servers in dielectric fluid, a liquid that does not conduct electricity, rather than cooling them with air conditioning.

    According to the report, Vector ONE supports up to one megawatt of computing power in 150 to 250 square feet, and the company says it allows computing in 70% less space than air-cooled equipment. No pricing, customers, shipment dates or energy-efficiency figures were given.

    Executive Summary

    Infinium is entering data center cooling with an immersion system, a design in which servers sit in tanks of non-conductive liquid that carries heat away from chips far better than air does. The product, sold under the company’s EdgeSites and Infinium Edge names, is pitched on two claims: it uses no water, and it packs up to a megawatt of computing into a footprint the size of a large room.

    Both claims land on live issues in AI infrastructure. AI servers run hotter and denser than conventional servers, pushing air cooling to its limits, and data center water consumption has become a flashpoint with local communities and regulators. A product that addresses density and water at once is well aimed.

    What the announcement does not yet show is the part that decides whether waterless cooling works at scale: how the system rejects a megawatt of heat to the outdoors, how much electricity that takes, and how its capacity holds up in hot weather, which is exactly when evaporative cooling earns its keep.

    A Megawatt in a Large Room Is the Real Headline

    The most concrete number in the announcement is density. One megawatt in 150 to 250 square feet works out to roughly 4,000 to 6,700 watts of computing per square foot of floor. That is far beyond what traditional raised-floor, air-cooled data halls are built to handle, and it is the kind of concentration modern AI hardware demands. Graphics-processor servers used to train and run AI models pack far more power into each rack than the general-purpose servers most facilities were designed around.

    Immersion cooling makes that density possible because liquid absorbs and moves heat far more effectively than air. The claim of 70% less space follows naturally: without the aisles, air handlers and spacing air cooling requires, servers can sit much closer together. For operators short on floor space, or trying to fit AI capacity into an existing building or a small edge site, that is a genuine advantage.

    Waterless Moves the Hard Problem Outdoors

    Immersion solves the problem of getting heat off the chip. It does not make the heat disappear. Every watt a server draws ends up as heat in the fluid, so a fully loaded Vector ONE has to shed up to a megawatt of heat continuously, and it has to do so from a very small footprint. That step, known as heat rejection, is where the water question is actually decided.

    Many large data centers use evaporative cooling because evaporating water is an extremely effective way to dump heat, especially in hot, dry weather. A system that uses no water must reject heat by dry means, typically fans pushing outside air across heat exchangers. Dry systems avoid water consumption entirely, but their capacity depends on outdoor air temperature: the hotter the day, the harder they work and the more electricity their fans draw. Immersion helps here, because the fluid can run warmer than the air in a conventional data hall, which widens the gap between fluid and outdoor air and makes dry rejection more practical. How much it helps is a question of engineering data Infinium has not published.

    This is why the density figure and the water claim are linked. Packing a megawatt into 250 square feet concentrates the heat-rejection burden, and the outdoor equipment, its size, noise, power draw and hot-day rating, becomes the component that determines whether the megawatt figure holds in July in Sacramento or Phoenix. Site developers in water-stressed regions, utilities sizing grid connections, and buyers comparing total energy costs are the people for whom that answer matters most.

    Water Is the Pressure Point, Energy Is the Trade-Off

    Positioning around zero water use is commercially astute. Data center water consumption has drawn scrutiny in drought-prone areas, and a cooling approach that removes water from the conversation can ease permitting and community relations. That value is real even before any efficiency numbers are considered.

    The efficiency claim as reported, that immersion cools servers more efficiently than air conditioning, is a comparison with air cooling, a fairly low bar for liquid systems. The more relevant comparison for AI-scale sites is against water-assisted cooling, where operators trade water for lower electricity use. The industry-standard way to express that trade is power usage effectiveness, or PUE, the ratio of total facility power to computing power, alongside water usage effectiveness. Neither figure accompanied the announcement, so the claim that Vector ONE is both waterless and efficient remains to be demonstrated.

    An Edge Product From an Unexpected Supplier

    Infinium’s core business is electrofuels, synthetic fuels made from renewable electricity, and the company has recently landed an airline fuel deal and begun work on what it calls the world’s largest electrofuel plant. A cooling product is a notable step sideways, though both lines of business sit at the intersection of energy and heavy industrial engineering.

    The EdgeSites and Infinium Edge branding, and the one-megawatt unit size, point toward modular and edge deployments rather than the hundred-megawatt campuses hyperscalers build. That is a sensible niche: edge sites are often in places where water hookups, space and cooling infrastructure are hardest to come by, and a self-contained unit that arrives ready to run fits those constraints. It also means Vector ONE competes with established immersion and modular data center vendors, where track record, server-maker support and service networks weigh heavily in purchasing decisions.

    Background

    Infinium is a Sacramento-based clean-fuel company that develops electrofuels, synthetic fuels produced with renewable electricity. It has announced an airline fuel supply deal and started construction on what it describes as the world’s largest electrofuel plant. The EdgeSites Vector ONE, marketed under its Infinium Edge name, marks its move into data center cooling.

    Immersion cooling is an established technique that has moved from niche uses toward mainstream interest as AI hardware pushes power density beyond what air cooling handles comfortably. At the same time, data center water consumption has become a siting and permitting issue in water-stressed regions, increasing demand for cooling approaches that avoid evaporative water use.

    Sources

    Source: Infinium unveils self-contained data center cooling system that uses no water (Sacramento Business Journal, July 27, 2026), reporting on Infinium’s EdgeSites Vector ONE waterless immersion cooling system.

  • Fort Bliss’s 1,384 Acres Show Military AI’s Hard Limit Is Power, Not Land

    Fort Bliss’s 1,384 Acres Show Military AI’s Hard Limit Is Power, Not Land

    TL;DR · 30-second read

    The Short Version

    The United States military is letting private companies build giant computer centers for artificial intelligence on its bases. One in Texas will cover more than two square miles of Fort Bliss. Another is planned for a Utah testing range.

    The catch is electricity. A local newsroom estimated the Texas site alone could use more power than all 460,000 homes and businesses on El Paso’s power system combined. Members of Congress from both parties now want the Pentagon to explain where that power and water will come from before building starts.

    Lawmakers from both parties are trying to attach conditions to the Defense Department’s program of leasing military land to private companies for AI data centers, Politico reported on July 25, 2026. The Army has signed two conditional agreements: Carlyle Group will build on 1,384 acres at Fort Bliss in El Paso, Texas, by 2027, and CyrusOne will build on 1,201 acres at Utah’s Dugway Proving Ground by 2029, according to an Army fact sheet. The Air Force has offered unused land on five installations.

    Most of the proposals would require briefings, studies or planning rather than stopping construction. A provision from Rep. Ken Calvert (R-Calif.) requiring DOD to brief Congress on community impacts before construction was adopted in the House Defense spending bill, and a provision from Rep. Cory Mills (R-Fla.) barring land deals for data centers with significant components made by U.S. adversaries is in the House-passed NDAA. Broader Democratic amendments, including one from Rep. John Garamendi (D-Calif.), were rejected.

    Executive Summary

    The Pentagon’s plan to host commercial hyperscale data centers on military bases, set in motion by President Trump’s executive order last year directing the department to identify suitable sites, has moved from policy to signed deals. The Army describes its Fort Bliss and Dugway projects as coming at “no upfront cost to taxpayers” and including “comprehensive behind-the-meter power and water solutions”, meaning the sites would generate or source their own electricity and water rather than draw on the local utility.

    That promise is now the center of the congressional debate. The measures gaining traction do not question whether the military can offer land; they ask the Defense Department to show, before construction, how these facilities will be powered and cooled without straining base infrastructure, local grids, or water supplies. For developers, that turns power and water planning from a project detail into a condition of doing business on federal land.

    The House and Senate still have to reconcile their versions of the defense authorization and spending bills, possibly after the November elections, so the final terms remain open.

    Land Is the Part the Military Can Give Away

    The Army’s pitch to developers is built on land: large, secured, already federally controlled parcels offered without an upfront cost to taxpayers. Fort Bliss alone puts 1,384 acres on the table, and Dugway another 1,201. Even supporters in Congress frame the benefit in land terms. Rep. Derrick Van Orden (R-Wis.) said he favors base siting if it means fewer data centers on farmland that could otherwise grow crops.

    But acreage is not what limits an AI data center. The binding constraint is electricity, and then water for cooling. El Paso Matters has estimated that the Fort Bliss facility could require more power than all of El Paso’s 460,000 electricity customers combined. Whether or not that estimate holds at full build-out, it sets the scale: a single campus of this kind can rival a mid-sized city’s demand. No amount of available land changes that arithmetic.

    That is why the Army’s promise of “behind-the-meter” power carries so much weight. Behind-the-meter means generation on the customer’s side of the utility connection, so the data center would not simply pull from the local grid. If it works, the developer absorbs the cost and risk of building a power plant. If it falls short, the load lands on the regional utility and its ratepayers, which is precisely the outcome lawmakers from both parties say they want the Pentagon to rule out in advance.

    Congress Is Asking for Proof, Not Stopping the Build-Out

    The legislative scorecard shows where the consensus sits. Proposals to halt or ban construction failed: Rep. Rashida Tlaib’s (D-Mich.) amendment to prohibit AI data centers on federal lands was rejected, as was a Senate Democratic amendment to block leasing until DOD finalizes a data center strategy. Garamendi’s pre-deal certification requirement, covering energy, water, noise, light, security and supply chains, was voted down in House Armed Services.

    What advanced is disclosure. Calvert’s provision, written into the House Defense spending bill, acknowledges that data centers “place significant strain on energy and water resources” and requires a pre-construction briefing on community impacts. A bipartisan Energy-Water package asks the Department of Energy to mitigate data centers’ effects on grid reliability and ratepayers. Even critics of Garamendi’s approach, such as Rep. Pat Harrigan (R-N.C.), suggested annual impact reports as an alternative. The live disagreement is not whether the Pentagon must account for power and water, but whether that accounting comes before a deal is signed or after.

    DOD officials argue the department has already accounted for these impacts and warn that added requirements could slow the military in a competitive AI race. That concern is legitimate; so is lawmakers’ complaint, voiced by Rep. Mike Levin (D-Calif.), that they have not received a briefing. Both claims could be tested quickly if the department published the power and water figures behind its agreements.

    The Supply Chain Clause May Bite Harder Than the Studies

    The provision with the most direct commercial consequence may be the one from Mills, now in the House-passed NDAA. It would bar DOD from providing land to data centers containing “significant components” manufactured by U.S. adversaries. An unnamed Army official told the Federal News Network that this would create an “unworkable standard” that could drive commercial partners away from Army land.

    Unlike a briefing requirement, a component rule reaches into the equipment bill of materials: servers, networking gear, power and cooling systems. How much it bites depends on how “significant” is defined and enforced, and on whether it applies to behind-the-meter generation equipment as well as computing hardware. For developers weighing base sites against private land, a sourcing rule that is hard to certify could matter more to the economics than any study requirement.

    Who Carries the Risk

    For Carlyle and CyrusOne, the emerging terms shift risk onto the developer: finance the facility, supply its own power and water, and, if Mills’ language survives conference, document the origin of key components. For base commanders, the question is whether on-site generation and water use interact with installation readiness. For neighboring communities such as El Paso, the stakes are grid reliability and electricity bills, the same concern driving the House Energy and Commerce Committee’s Ratepayer Protection Act, H.R. 9340.

    The broader lesson for anyone siting AI infrastructure is that federal land does not bypass the power question. It relocates it, and adds a layer of public accountability that private sites do not face.

    Background

    AI data centers pack large numbers of power-hungry processors into a single site, and their electricity and cooling needs have become a flashpoint for utilities, regulators and communities across the United States. Hyperscale facilities, the largest class of data center built for cloud and AI workloads, can draw power on the scale of a small city and often use significant volumes of water for cooling.

    The Defense Department entered this market after a presidential executive order last year directed it to identify military sites suitable for AI infrastructure. The Army’s model leases base land to private developers, who build and operate the facilities, and the Air Force has offered unused land at five installations. Carlyle Group is an investment firm; CyrusOne is a data center developer and operator.

    Sources

    Source: The Pentagon wants to build data centers. Congress would like a word. (Politico) — bipartisan congressional scrutiny of Defense Department land leases for AI data centers at Fort Bliss, Dugway and Air Force installations.

  • 55 Oklahoma Data Centers, Zero Water Permits: AI Cooling Runs on Utility Contracts

    55 Oklahoma Data Centers, Zero Water Permits: AI Cooling Runs on Utility Contracts

    TL;DR · 30-second read

    The Short Version

    Oklahoma has about 55 data centers, the giant warehouses of computers behind apps, websites and artificial intelligence. Not one has applied for a state permit to draw water.

    They buy water from local utilities like any other customer, so the state does not track how much they use. One Google site uses as much water each year as 10,000 homes, and most of it evaporates.

    With a $15 billion campus proposed near Yukon in a state hit by years of drought, neighbors are asking questions developers are not yet required to answer.

    None of the 55 data centers that advisory firm Baxtel lists in Oklahoma has applied for a state water permit, according to reporting by Investigate Midwest published in The Oklahoman. They buy water as customers of municipal utilities, rural water districts or industrial parks that already hold water rights, so their consumption sits largely outside state oversight. Senate Bill 259, signed by Gov. Kevin Stitt in May, allows groundwater permits for data centers only if they use water-conserving, recycling cooling systems, but it does not reach facilities that buy water instead of seeking permits.

    The gap is drawing attention as Atlanta-based Beltline Energy proposes a $15 billion, 1,000-megawatt campus of 15 buildings on 480 acres straddling Oklahoma City and Yukon. Yukon is considering selling the project up to 2.5 million gallons of wastewater per day, while Beltline has requested extensions on the water agreement and has not said which cooling system it would use.

    Executive Summary

    Oklahoma’s newest data center water rule targets the one route data centers do not use. State permits govern taking water directly from aquifers and rivers; data centers instead contract with local suppliers. “So far, we have not had any permits issued specifically to data centers,” said Julie Cunningham, director of the Oklahoma Water Resources Board.

    The practical consequence is that the decisions that determine how much water an AI campus consumes, including its volume, its source and whether it evaporates or recycles cooling water, are being made in municipal supply agreements rather than state permits. Yukon’s pending contract with Beltline is a live example.

    Closing the permitting gap would not by itself produce usage data. The state relies on self-reported figures, metering requirements have failed twice, and the water board reported fewer than 20 staff in 2025. Rep. Carl Newton, the author of SB 259, says a new bill next year will address data centers drawing groundwater through a secondary source.

    Why the Permit Rule Misses the Meter

    SB 259 attaches a sensible condition to groundwater permits: data centers can get one only if their cooling systems are designed to conserve and recycle water. But a permit is only required when a user withdraws water itself. A data center that buys from a city, a rural water district or an industrial park holding industrial water rights is treated as an ordinary customer of that system, and the state never sees an application. That is why a statewide count of zero permits sits alongside 55 listed facilities.

    The real regulatory instrument is therefore the supply contract. Google’s Pryor data center, the state’s largest, buys water from the state-owned MidAmerica Industrial Park, which draws and treats it from the Neosho River. Beltline’s Yukon purchase agreement hinges on a separate water agreement with the city. Whoever negotiates those contracts, usually a municipal utility or city council, effectively decides volume, source and whether the water is potable or treated wastewater. The state’s conservation standard never enters the room.

    This matters for everyone on the supply side. City water utilities are becoming the de facto gatekeepers for AI cooling, often with small staffs and without statewide guidance. Developers face a patchwork of local terms rather than one state rulebook. And residents who want answers, like Yukon-area neighbor Pencia Truhan, who said developers “don’t have to tell us what they’re going to do about water,” find no state filing to consult.

    The Cooling Choice Is Also a Power Choice

    Cooling design is where water and electricity trade off. Open-loop, or evaporative, systems like Pryor’s lose water to the atmosphere: Google reports the site consumes 1.1 billion gallons a year, about the annual use of 10,000 American households, and returns roughly 275 million gallons to the Neosho River. That leaves about 825 million gallons evaporating each year. Closed-loop systems recirculate water, and air-cooled systems use little water but significantly more electricity.

    For Beltline’s proposal, that trade-off lands on an unusually large base. A 1,000-megawatt campus would, at full capacity, draw roughly as much electricity as Oklahoma City’s average use and more than double the demand of Google’s Pryor facility. Choosing air cooling to spare local water would push that electricity figure higher; choosing evaporative cooling would do the reverse. Because the cooling system has not been disclosed, neither the water nor the full power burden can yet be estimated.

    Yukon’s Math: Wastewater, Wells and a 2035 Deadline

    Yukon’s planning memo describes selling Beltline up to 2.5 million gallons of wastewater a day, and officials have promised the project will not rely on drinking water. At full volume that is about 900 million gallons a year, comparable in scale to what Pryor evaporates annually. Using treated wastewater is a common way to spare potable supply, but the sale still commits a resource the city may want for other purposes.

    The city’s supply position is already tight. Yukon relies on 15 leased wells in the Garber-Wellington Aquifer plus purchases from Oklahoma City, and those leases expire in 2035. A city-commissioned study projects its 27,300 residents will grow by about 23% over 25 years, in Canadian County, the state’s fastest-growing county. Against that, Beltline-commissioned studies project 450 permanent jobs and $543.12 million in tax revenue over 25 years, figures that potential tax abatements would significantly reduce.

    Measurement Is the Harder Fix

    Even a closed loophole would leave a data gap. The Oklahoma Water Resources Board relies on self-reported water use. Newton’s original bill would have required commercial groundwater users to install meters; that provision was removed after opposition from Panhandle irrigation groups, and Stitt vetoed similar legislation in 2023 after the Oklahoma Farm Bureau and others argued it infringed on private property rights.

    Capacity is the other constraint. In 2025 the board reported fewer than 20 staff handling an average of 250 permit applications and amendments a year, plus investigations and fieldwork, and its 140-page Water Demand Forecast from last October does not mention data centers. Cunningham said the agency is working to build expertise. Until measured data exists, planners in a drought-stressed state are forecasting water demand without one of its fastest-growing users in the model.

    Background

    Data centers house the servers behind everyday online services, and the newest hyperscale facilities built for artificial intelligence concentrate enough computing to generate heat on an industrial scale. Removing that heat often uses large volumes of water, which is why cooling design has become a siting issue alongside land and power. Oklahoma already hosts one of Google’s largest facilities in Pryor, where the company outlined plans addressing power and water for new sites, and the state is drawing further proposals.

    Beltline Energy, based in Atlanta, began as a renewable energy developer that secured land and developed solar projects before selling them to investors, and it is applying a similar model to data centers. It has developed more than a dozen solar farms but lists no completed data center projects. Its Oklahoma proposals, in Yukon and Oklahoma City, Piedmont and Luther, arrive as the state’s water regulator, which relies on self-reported usage data, works to develop expertise in the sector.

    Sources

    Source: Loophole leaves data center water consumption in Oklahoma largely untracked (The Oklahoman), on how Oklahoma data centers buy water from utilities outside state permitting, and the proposed Beltline Energy campus near Yukon.

  • Project Tango’s 5-1 Denial Shows AI Campuses Can Outgrow Local Zoning Codes

    Project Tango’s 5-1 Denial Shows AI Campuses Can Outgrow Local Zoning Codes

    TL;DR · 30-second read

    The Short Version

    County leaders in Palm Beach County, Florida, voted 5 to 1 to turn down Project Tango. It was a giant complex of computers for artificial intelligence, planned near about 2,400 homes and an elementary school.

    A big worry was a constant low hum, day and night. The builders said cooling would need a one-time fill of about 650,000 gallons of water, roughly one Olympic swimming pool.

    The bigger lesson is that local building rules are struggling to decide what these new facilities even are. The developer can try again.

    Palm Beach County commissioners on Wednesday, July 15, 2026, voted 5-1 to deny without prejudice Project Tango, a proposed AI data center campus in Loxahatchee, WPEC (CBS12) reported. The vote followed hours of debate over low-frequency noise, water use, traffic and compatibility with a rural area that opponents said now includes about 2,400 homes and Saddle View Elementary School. Commissioner Maria G. Marino cast the lone vote in favor. Mayor Sara Baxter recused herself on the County Attorney’s advice because of her prior public statements opposing the project.

    The request before the board covered Phase 2 of the site: 280,000 square feet of data and information processing, 148,000 square feet of cooling-related utility space and about 1.15 million square feet of warehouse. The applicant projected a $34.5 billion asset at build-out over six to seven years and about $561 million in tax revenue at build-out.

    Executive Summary

    Project Tango did not fail on a single number. It failed because commissioners could not agree with the applicant on what the project was. The developer’s attorney argued that data processing was already a permitted use on a site approved years ago for economic development. County staff answered that the application would add roughly 1.5 million square feet to that approval. One commissioner called the proposal “an AI hyperscale whatever” and questioned whether the county’s definitions had kept pace.

    That dispute is the part that matters beyond Palm Beach County. Many AI data center plans rely on land entitlements granted for warehouses, light industry or generic economic development. Project Tango shows a local board declining to treat those older approvals as covering a 24-hour computing campus. The questions it pressed hardest, on low-frequency noise and on water, are ones existing codes were not written to answer.

    Because the denial was without prejudice, the applicant can return with a revised plan. The hearing showed fairly clearly what the next attempt would need to bring: independent expert evidence, a named end user, and firmer answers on noise and water.

    An AI Campus the Zoning Code Wasn’t Written For

    The sharpest exchange of the hearing was about categories rather than engineering. Applicant attorney Brian Seymour described the request as an “allocation of permitted uses, not a new use,” noting that data and information processing is already allowed under the county’s code for the site. County staff rejected that framing directly: “That is incorrect. That is why we are here today. This application is to add square footage.” Staff said the site is approved for 2,020,000 square feet of Economic Development Center uses and that the request would add about 1.5 million square feet to the master plan. Opponents described the result as a 3.6-million-square-foot campus.

    Commissioner Joel Flores put the underlying problem plainly: “This is not exactly a data center. This is something new.” He said he was struggling with whether the county was relying on older definitions “just because they haven’t been updated.” The applicant argued the campus should be treated as light industrial and noted it would replace existing heavy industrial operations, including asphalt and concrete plants. By conventional land-use logic, that is a reasonable argument, since a data hall generates little truck traffic or dust. But a hyperscale AI campus (a very large facility built to run AI workloads at scale) runs around the clock, needs substantial cooling equipment and draws significant electricity. Those traits do not map neatly onto a code category written for offices, warehouses or light manufacturing.

    This matters for developers and investors who treat an existing entitlement as a de-risked asset. Project Tango is a single case and should not be read as a statewide trend. It does show that a board can decline to extend a years-old approval to cover an AI campus, even when the use is technically listed, if it concludes the scale and operating profile are materially different from what was approved. Sites whose value depends on legacy economic-development or industrial zoning carry that risk until local codes define AI facilities explicitly.

    Closed-Loop Cooling Shifted the Water Question Instead of Settling It

    The applicant’s water figures for the computing itself were modest. Its engineer said the campus would use a closed-loop cooling system, which circulates the same water rather than evaporating it daily. The data processing portion would use about 1,696 gallons per day, mostly for restrooms, sinks and kitchens. For comparison, county Water Utilities Director Ali Bayat said the neighboring Arden community uses about 400,000 to 500,000 gallons of drinking water a day. On that basis, daily data center use would be well under 1% of the neighborhood’s use.

    Scrutiny moved to other parts of the plan. The system would need a one-time fill of about 650,000 gallons, roughly a day and a half of Arden’s consumption. The warehouse portion was projected at about 50,000 gallons a day, around a tenth of Arden’s daily use. When Commissioner Maria Sachs asked who would be using it, Seymour said he did not know the headcount because that information came from the contract purchaser. Flores also asked what happens if the loop water must be drained or becomes contaminated. The applicant’s environmental health expert said it would be collected and disposed of off-site under Florida rules.

    The lesson for operators is that closed-loop designs can defuse the familiar evaporative-cooling objection, but that alone does not end the conversation. Boards will ask about every gallon on the site plan. A number without a named user or an explanation reads as a gap, whatever the cooling design.

    Why Meeting the Noise Standard Didn’t End the Noise Debate

    Low-frequency noise drew one of the longest lines of questioning. The applicant’s experts said the project would meet county noise standards and keep levels near Arden and the school within existing ambient levels. Acoustics expert Dr. Norm Bronner acknowledged that low-frequency noise “will exist,” but said it likely would not be particularly noticeable at the predicted levels. Commissioners focused on whether a constant hum would be audible to residents and students. “We’re not talking about music,” Sachs said. “We’re talking about a hum that resonates.”

    The one measurement taken in the chamber illustrates why compliance with the standard did not settle the matter. During a quiet moment, the applicant’s expert recorded 43.9 dBA and 59.8 dBC. A-weighted decibels (dBA), common in noise rules, discount low frequencies roughly as the human ear does at moderate volume. C-weighted readings (dBC) count low frequencies more fully. A gap of about 16 decibels in an ordinary quiet room shows how much low-frequency energy an A-weighted limit can leave out. That is the kind of sound a round-the-clock campus of fans and chillers produces.

    Seymour offered pre- and post-operation noise studies, with shutdown or mitigation if the project failed its conditions. That is a meaningful commitment on paper. However, it asks a board to approve first and verify later. Sachs said she could not accept the project without a scientist able to vouch for a comparable operating facility. That standard points developers toward bringing measured data from existing sites rather than modeled projections alone.

    What the Denial Leaves on the Table

    The economic case was substantial: a projected $34.5 billion asset at build-out over six to seven years, much of it in equipment and computers, and about $561 million in tax revenue at build-out. Commissioner Marino, the lone dissent, said, “I would say we need this.” Other commissioners did not dispute the size of the investment. They said the evidence on compatibility was incomplete, and Vice Mayor Woodward said approval would require “a lot more experts, conditions.”

    Denial without prejudice keeps the project alive in principle. A resubmission would likely need to resolve the square-footage dispute with staff, identify the end user, explain the warehouse water figure and bring independent low-frequency noise evidence. The hearing also carried signs of how heated the local debate had become. Flores disclosed that his office had received threatening calls, and a court had denied an emergency request to block the hearing. Any developer returning to this site, or pursuing a similar one elsewhere in Florida, should expect a long and closely examined process.

    Background

    The Project Tango site in Loxahatchee was approved in 2016 for Economic Development Center uses and currently hosts heavy industrial operations, including asphalt and concrete plants. Residential growth has since surrounded it. The Arden community and Saddle View Elementary School now sit nearby, and opponents put the number of surrounding homes at about 2,400. Residents said they learned of Project Tango about eight months before the vote.

    In Florida, land-use decisions like this one are quasi-judicial. Commissioners act somewhat like judges, weighing evidence presented at a hearing, and they must avoid appearing to have prejudged the case. The Project Tango fight reflects a wider pattern in which AI data centers, designed to run power-hungry computing around the clock, are testing local zoning codes written before such facilities existed at this scale.

    Sources

    Source: Palm Beach County commissioners reject controversial Project Tango AI data center (WPEC): CBS12 coverage of the July 15, 2026 commission vote on the Loxahatchee AI data center proposal.

  • Meta AI Data Center Linked to Rare Bacteria in a City Water System

    Meta AI Data Center Linked to Rare Bacteria in a City Water System

    Forbes reported on July 10, 2026 that a Meta AI data center has been linked to rare bacteria detected in a city’s water system — a striking escalation of the long-running debate over how much water AI data centers consume, into a question about what they may put back. The headline alone frames the story; the publicly circulated material does not name the city, identify the bacteria, or explain the mechanism of the alleged link.

    The report lands as Meta and its hyperscale peers are in the middle of the largest data center construction wave in history, much of it cooled — directly or indirectly — with municipal water.

    Executive Summary

    According to Forbes, a Meta data center built to serve the company’s artificial-intelligence workloads has been connected to the presence of a rare bacteria in the water system of a nearby city. If substantiated, this would mark a significant shift in the data center water debate: for years the argument has centered on quantity — how many millions of gallons evaporative cooling draws from local supplies — while this story raises a quality and public-health dimension.

    Why it matters: water is the quiet dependency of the AI buildout. Many large data centers use evaporative cooling, in which water absorbs server heat and is partially evaporated away, because it is dramatically more energy-efficient than pure air-based cooling. That efficiency comes with entanglement — data centers become major customers of, and in some configurations discharge back into, the same municipal systems that serve residents.

    Important caveat up front: ‘linked’ is doing heavy lifting in this headline. The available material does not establish causation, name a health authority’s finding, or describe Meta’s response. This article analyzes the stakes while flagging exactly what remains unverified.

    When the Water Debate Becomes a Public-Health Story

    Data center water use has been a community flashpoint for several years, but the framing has been almost entirely volumetric: how many gallons per day, whether aquifers or reservoirs can sustain it, and whether households pay more as a result. A bacteria-in-the-water-system story changes the emotional and regulatory register entirely. Volume disputes are negotiated in rate cases and zoning hearings; contamination questions summon health departments, environmental regulators, and — fairly or not — a much deeper reservoir of public anxiety.

    Mechanically, there are plausible pathways for a large industrial water user to interact with a municipal system’s water quality: heavy draws can change pressure and flow patterns in distribution pipes, warm discharge or blowdown water (the mineral-concentrated water periodically flushed from cooling systems) must be treated and returned somewhere, and large open-loop cooling towers are themselves known habitats for waterborne bacteria such as Legionella. To be clear, none of these mechanisms is confirmed in this case — the source material does not say which, if any, applies. But they explain why a ‘link’ claim is at least technically conceivable rather than absurd on its face.

    What ‘Linked’ Does and Does Not Establish

    The scrutiny has to run in every direction. For the reporting: what evidence supports the link — sampling data, a utility investigation, a health-department finding, or expert inference? Correlation between a new industrial water customer and a new detection is not causation; municipal systems detect unusual organisms for many reasons, including aging pipes, source-water changes, and improved testing. For Meta: what water does the facility draw, what does it discharge, under what permit, and what monitoring does it publish? For the utility and local officials: what does the testing history show before and after the facility came online, and has anyone actually been harmed?

    The honest answer, based on what has circulated publicly, is that we cannot yet distinguish between three very different stories: a genuine contamination pathway traced to the facility, a coincidental detection amplified by the data center’s high profile, or something in between — for example, system stress that made an existing problem visible. Each has radically different implications, and readers should hold all three open until primary documents surface.

    The Economics of Water in the AI Buildout

    Hyperscalers use water because physics and economics reward it. Evaporative cooling can cut a facility’s cooling energy dramatically compared with mechanical chillers, lowering both operating cost and the grid capacity a site must secure — often the binding constraint on AI campuses measured in hundreds of megawatts. The industry’s own metric, water usage effectiveness (WUE), exists precisely because operators know the trade-off is real: save electrons, spend water.

    That calculus is shifting. Direct-to-chip liquid cooling and closed-loop systems — which recirculate a fixed volume of water or coolant rather than continuously evaporating fresh supply — are increasingly standard for dense AI hardware, and several operators have announced designs that consume little or no water for cooling. A public-health controversy, even an ultimately unproven one, accelerates that shift by adding reputational and permitting risk to the cost side of the evaporative-cooling ledger. Communities negotiating with data center developers now have one more reason to demand closed-loop designs, discharge transparency, and independent water-quality monitoring as conditions of approval.

    Winners, Losers, and the Precedent That Matters

    If the link is substantiated, the losers are obvious: the affected community first, then Meta’s siting pipeline, and then every operator whose pending permits get re-examined through a public-health lens. The beneficiaries would be vendors of waterless and closed-loop cooling, water-treatment and monitoring firms, and jurisdictions that wrote strong discharge and reporting requirements into their agreements and can now point to them.

    If the link is not substantiated, the story still matters, because permitting battles run on narrative as much as data. The industry has often been slow to publish site-level water data, treating it as competitively sensitive; that opacity leaves a vacuum that headlines fill. The durable lesson either way is that transparency is cheaper than suspicion: operators who publish withdrawal, discharge, and monitoring data before a controversy get to argue from their own numbers rather than someone else’s framing.

    Background

    Meta operates one of the world’s largest data center fleets and has been expanding it aggressively to support its artificial-intelligence ambitions, with new campuses whose power demands are measured in the hundreds of megawatts and beyond. Like its hyperscale peers, the company has faced recurring community scrutiny over local resource impacts — power, land, and especially water — and, like those peers, has publicized water-restoration commitments intended to offset consumption.

    Until now, the water controversy around AI infrastructure has been overwhelmingly about scarcity: whether local systems can supply large evaporative-cooling loads without straining households and agriculture. A report tying a facility to bacteria in a municipal system — whatever its ultimate substantiation — moves the debate from resource competition to public health, a categorically more sensitive terrain for operators, regulators, and residents alike.

    Source: Meta AI Data Center Linked To Rare Bacteria In City’s Water System — Forbes report, July 10, 2026, connecting a Meta AI data center to a rare bacteria detection in a municipal water system.

  • WSJ: AI Data Centers’ Water Use Far Exceeds What Tech Giants Disclose

    WSJ: AI Data Centers’ Water Use Far Exceeds What Tech Giants Disclose

    The Wall Street Journal published an investigation on July 3, 2026, reporting that AI data centers consume far more water than most major technology companies publicly acknowledge. The reporting targets the gap between the industry’s sustainability disclosures and the actual water draw of the facilities powering the AI boom — a gap with direct consequences for the communities, utilities, and regulators hosting these sites.

    Executive Summary

    According to the Journal’s headline finding, the water consumed by AI data centers substantially exceeds the figures most tech giants report. That claim lands at a sensitive moment: hyperscale operators are racing to build AI capacity at unprecedented scale, and many of the fastest-growing markets for that capacity are in water-stressed regions where every megawatt of cooling has a hydrological cost.

    The significance is less about any single number and more about trust in the measurement system itself. Data center operators have spent a decade building sustainability reporting frameworks — water usage effectiveness metrics, replenishment pledges, “water positive” targets. An investigation asserting that disclosed figures materially understate real consumption challenges the credibility of that entire apparatus, and will sharpen scrutiny from permitting authorities, investors, and enterprise customers alike. It is worth noting up front that the material available at publication is the Journal’s headline claim; the underlying methodology and company-by-company figures sit behind the investigation itself, so our analysis focuses on how such a gap can exist and what it would mean if borne out.

    Why Water Is the AI Boom’s Quiet Constraint

    Data centers use water primarily for cooling. Evaporative systems — the most energy-efficient way to reject heat in many climates — work by evaporating water to carry heat out of the building, which means the water is genuinely consumed rather than borrowed and returned. AI workloads intensify this: training and inference clusters pack far more power into each rack than traditional enterprise computing, and every kilowatt of electricity ultimately becomes heat that must go somewhere.

    Power availability has dominated the AI infrastructure conversation, but water is the constraint that most directly touches neighbors. A community can rarely see the grid strain a campus causes; it can see reservoir levels, well permits, and municipal supply contracts. That visibility is why water — more than carbon — has become the flashpoint in local data center opposition, and why a disclosure gap, if substantiated, matters commercially and not just reputationally.

    How a Disclosure Gap Can Exist Without Anyone Lying

    Water accounting has honest ambiguities that reporting can exploit or obscure. “Withdrawal” (water taken in) and “consumption” (water evaporated and lost) are different numbers. On-site cooling water is different from the much larger volumes evaporated at the power plants generating a facility’s electricity — a burden that rarely appears in corporate water figures. Companies may report global averages that dilute stress in specific basins, disclose only company-owned sites while leasing heavily from colocation providers, or treat site-level data as a trade secret in agreements with local utilities.

    Each choice can be individually defensible and collectively misleading. If the Journal’s investigation shows real draw far above disclosed figures, the likeliest mechanism is not fabrication but selective scope: what gets counted, where, and at what level of aggregation. That is precisely why the methodology on both sides deserves scrutiny — an investigation comparing utility records of total withdrawal against corporate disclosures of net consumption would find a large gap even where reporting is technically accurate. Neither the companies’ frameworks nor the investigation’s comparisons should be taken on trust without seeing definitions aligned.

    Winners, Losers, and the Coming Transparency Squeeze

    If disclosure practices tighten — voluntarily or by mandate — the advantage shifts to operators who engineered for water frugality before it was scrutinized: closed-loop liquid cooling, dry coolers, air-side economization in suitable climates, and treated wastewater sourcing. Vendors of direct-to-chip and immersion cooling gain a stronger sales narrative, since liquid cooling at the rack can pair with water-free heat rejection outside. Operators dependent on open evaporative cooling in arid, fast-growing markets face the hardest repricing, because retrofits are costly and permitting timelines are long.

    Enterprise buyers and investors are the other lever. Cloud and colocation contracts increasingly carry sustainability reporting clauses, and a credible investigation gives procurement teams grounds to demand site-level water data rather than glossy aggregates. For host communities, the practical effect is likely to be harder-edged development agreements: metered disclosure requirements, drought curtailment provisions, and consumption caps as conditions of approval. The industry can resist that trend or get ahead of it; the second option is cheaper.

    Background

    Water has trailed energy as the second axis of data center sustainability for over a decade. Major operators publish water metrics alongside “water positive” replenishment pledges — commitments to restore more water to stressed basins than their operations consume. Those frameworks were designed in the era of conventional cloud computing; the AI buildout that accelerated from 2023 onward brought far denser facilities, faster construction, and expansion into hot, dry regions where land and power are cheap but water is contested.

    Local friction has grown in step. Communities from the American Southwest to Europe and Latin America have challenged data center water allocations, and operators have responded with a mix of reclaimed-water sourcing, liquid cooling adoption, and — critics argue — selective disclosure. The Journal’s investigation lands squarely on that last point, testing whether the industry’s reported numbers describe the facilities actually being built.

    Source: AI Data Centers Use Far More Water Than Most Tech Giants Report — Wall Street Journal investigation, July 3, 2026, as syndicated via Google News.

  • Amazon’s 7x Water Claim Rests on Hotter Servers, a Test for AI-Era Cooling

    Amazon’s 7x Water Claim Rests on Hotter Servers, a Test for AI-Era Cooling

    TL;DR · 30-second read

    The Short Version

    Amazon says the buildings that run its websites, apps and artificial intelligence services use about one-seventh the water of a typical facility of their kind.

    The main trick is letting the computers run warmer. Outside air cools the buildings about 90% of the time. Water is used only when it is hotter than about 85 degrees Fahrenheit outside.

    This matters because these buildings are multiplying, and their neighbors want to know how much local water they take. The open question is whether the newest artificial intelligence chips, which Amazon says needed a new kind of liquid cooling, will let that approach last.

    Amazon said in a June 11, 2026 post on its About Amazon site that its global data center operations used 0.12 liters of water per kilowatt-hour (L/kWh) in 2025. The company puts that at more than seven times better than an industry average of 0.84 L/kWh and says it is a 52% improvement since 2021. It withdrew about 2.5 billion gallons of water across its global data center footprint in 2025.

    Amazon credits two things for the result. The first is free-air cooling, which it uses about 90% of the time. The second is higher server temperature limits, so that evaporative cooling runs only when outside air is above roughly 85°F. The company also said it is 75% of the way to its 2030 water-positive goal and that it runs 26 facilities on 100% reclaimed water, with 130 more contracted.

    Executive Summary

    Amazon has published a headline water-efficiency figure for its data centers: 0.12 liters of water for every kilowatt-hour of energy in 2025. It set that against an industry average of 0.84. The company explains how it got there. It relies on outside air for most cooling, uses evaporative cooling only in the hottest hours, and has spent several years raising the temperatures its servers are allowed to run at. It says this cut water use without raising hardware failure rates.

    The figure matters because water has become one of the main local questions asked of new data center campuses. Amazon’s explanation also shows that water efficiency is a set of engineering trade-offs, not a fixed property of a building. The company chose to use some water on hot days rather than run chillers, which it says need 25% to 35% more electricity at the moments the grid is most stressed.

    Two things are harder to assess. One is the comparison itself: Amazon did not publish how the 0.84 average was built or on what basis each peer’s figure is measured. The other is the future. Amazon says denser AI chips already required a custom liquid cooling system, so the air-first approach behind the 7x figure now has to hold up as AI capacity grows.

    The Water Number Is Really a Temperature Number

    Amazon’s 0.12 liters per kilowatt-hour did not come from a new water technology. It came from deciding how rarely to use water at all. About 90% of the time, Amazon says, its data centers use free-air cooling. Outside air is drawn past the servers and pushed back out, with no water involved. Water comes into play only through evaporative cooling. In that process, hot air passes through a water-soaked medium and cools by five to 10 degrees as the water evaporates. Amazon now switches that on only when outside air exceeds roughly 85°F.

    That threshold is the lever. Every degree of heat the servers can tolerate removes hours from the evaporative season, so raising operating temperatures cuts water use directly. Amazon’s own evidence is specific:

    • Two identical data centers on the same campus, one running hotter, differed by about 50% in water use.
    • Northern Virginia, its largest region by IT load (the power drawn by the computing equipment itself), cut water use 42% year over year while demand grew.
    • Thousands of hours of campus data showed no increase in failure rates at the higher temperatures.

    Those results fit the 52% efficiency improvement Amazon reports since 2021.

    The same logic is why this is a test for AI-era cooling. The approach depends on air being able to carry heat away from the servers. Amazon itself says denser, more powerful AI chips required a completely custom liquid cooling system. It has not said how much of its fleet now runs that way, whether those systems rely on evaporative water on hot days, or how a growing share of AI capacity will move the 0.12 figure. The air-first playbook behind the 7x gap was proven on the fleet Amazon has run since 2021. Whether it carries over to high-density AI halls is the next data point to watch.

    Water or Watts: The Trade Behind the Ratio

    Amazon is explicit that a low water number is partly a choice about electricity. The alternative it names is chillers, which work like giant air conditioners and, by Amazon’s figures, typically need 25% to 35% more electricity. The timing of that extra load is the problem. It arrives in the hottest hours, when household air conditioning is already straining the grid. Amazon concluded it is better to spend some water on those days than to add power demand at the peak.

    That is a defensible engineering position, and it cuts against a simple reading of water metrics. An operator could report a lower water ratio by running chillers, which shifts the burden onto the grid and, depending on how that electricity is generated, onto water used off site. Conversely, a site that uses more water may be sparing a stressed grid. For utilities and local planners, the useful question is how much water and how much power a campus uses together at the peak hour, not either one in isolation.

    Amazon did not quantify the grid side of its trade. It has not said how much peak demand evaporative cooling avoids across its fleet, or how many hours a year its sites in hot regions exceed 85°F. Without those figures, the argument rests on the chiller penalty range alone.

    Why 0.12 and 0.84 Are Hard to Line Up

    Liters per kilowatt-hour is the industry’s standard water-efficiency ratio, often called water usage effectiveness. It divides the water used for cooling by the energy consumed by the IT equipment. Amazon describes it as water per unit of compute, but the denominator is energy, not work done. A fleet running more efficient chips gets more computing out of each kilowatt-hour, and the metric does not capture that in either direction.

    The 7x claim depends entirely on the 0.84 industry average. Amazon’s chart cites sustainability reports and blogs from Microsoft, Google and Meta alongside its own report. The company did not publish how 0.84 was derived: which operators it covers, how they were weighted, or whether each figure measures water withdrawn (taken from a source) or water consumed (evaporated and not returned). Large operators do not all report water the same way, so a like-for-like reading requires knowing which basis each number uses.

    Scope matters too. Amazon’s absolute figure, about 2.5 billion gallons in 2025, is a withdrawal number for its global data center footprint. The 2% year-over-year decline it cites applies only to sites it owns and operates directly. The company did not say whether the 0.12 ratio is based on withdrawal or consumption, or whether leased facilities are included. None of that makes the claim wrong. It does mean the 7x multiple is Amazon’s own calculation rather than a figure a reader can reproduce from peers’ reports.

    Replenishment and Reclaimed Water Carry the Local Story

    Efficiency is only half of Amazon’s water case. The company has committed to being water positive by 2030, meaning it returns more water to communities than its data center operations use. It says it is 75% of the way there, returning 3 gallons for every 4 used in 2025. It has announced more than 50 projects that are expected to return over 5.8 billion gallons a year once fully implemented, which is more than twice its 2025 withdrawals. Examples include:

    • storing Columbia River winter flows in an aquifer in Hermiston, Oregon;
    • a runoff pipeline in Pina del Ebro, Spain;
    • watershed restoration near Guadalajara, Mexico.

    Replenishment is an accounting balance. Its value to a given town depends on whether the returned water lands in the same basin the data center draws from. Reclaimed water addresses the local question more directly, because it replaces drinking water with treated wastewater at the site itself. Amazon says 26 facilities already run on 100% reclaimed water, more than any other cloud provider, and 130 more are contracted. It has also funded infrastructure and helped with permitting for programs in Mississippi, Hong Kong and Indonesia. If those 130 facilities come online, reclaimed supply may matter as much to neighbors as the headline efficiency ratio.

    Background

    Amazon operates one of the world’s largest data center fleets, mostly to run Amazon Web Services (AWS), its cloud computing business. Data centers convert nearly all the electricity they use into heat, and removing that heat is where most of their water goes. The industry commonly measures water efficiency as liters of water per kilowatt-hour of IT energy, a ratio known as water usage effectiveness, or WUE.

    Amazon has committed to being water positive by 2030 and has expanded its use of reclaimed water from wastewater treatment plants. Amazon says data centers account for less than 0.5% of global industrial water use. Still, where a campus draws its water matters to the surrounding community, and Amazon says its water team is particularly focused on water-scarce areas.

    Sources

    Source: Amazon’s data centers are 7x more water-efficient than the industry average. Here’s how we do it. (About Amazon): Amazon’s account of its 2025 data center water efficiency, cooling methods, and progress toward its water-positive goal.