Grist28%

Nebraska wants data centers to come clean about water usage 22%

By Anila Yoganathan23%

7/15/2026, 1:00:00 AM

BS Summary: This article contains 26 faulty reasoning types, including Framing Effect, Negativity Bias, and Indoctrination, with Appeal to Authority as the most egregious example at 21.7% saturation with 157 hits. Analysis detected 1,240 faulty-reasoning hits from 722 analyzed words, generating a BS Score of 35.6% and a BS Rank of 22% (17,152 of 21,887 articles). This article is better (less manipulative) than 78.40% of the article peer group.

Often seen as a black box of information, data centers in Nebraska will be forced to reveal more about their operations, like their annual water use and power demand, to the state, following the recent passing of a new law by the Nebraska Legislature. 
Jesse Bradley, director of the Department of Water, Energy, and Environment, said the state agency will then see what information gaps remain, but that the legislation is a “great start” and will help with future planning. 
In addition to electricity production, water has emerged as a point of contention as companies look to build more data centers in Nebraska. 
Local residents, researchers, and regulators worry that new data centers could bring about water shortages in a state where water availability can vary widely and where wide swaths of this agricultural state are suffering through extreme drought. 
For now, the best available information about how much water data centers use comes directly from the data center companies themselves  if they choose to be transparent. 
For instance, in Nebraska, there isn’t even an official count of how many data centers there are in the state. 
Of the ones that have reported their water usage, the amounts vary. 
Google’s Nebraska data centers consumed about 732 million gallons of water in 2025, according to the company. 
Google, a subsidiary of Alphabet, expects its water consumption from data centers to grow. 
From 2020 to 2024 , Meta’s 4 million-square-foot Sarpy County data center withdrew anywhere from 26.7 million gallons to 37.5 million gallons from the local water supply, depending on the year. 
Data centers use water to cool the buildings and the computer servers inside. 
Keeping everything at optimal temperatures ensures the equipment doesn’t malfunction. 
Some cooling methods, like evaporative cooling systems, typically use large amounts of water. 
Air-cooled chiller systems, however, deploy a “closed loop” containing water, a chemical coolant, or sometimes both and can operate without needing to be replenished for years. 
While closed loop systems use less water, they tend to use more electricity  the production of which can also require water. 
“What’s best?” 
said Eric Masanet, a University of California, Santa Barbara engineering professor. 
“It depends on the data center, its design, the local climate, if you have enough water, if you have enough power, what people want, what they’re willing to devote their resources to.” 
A swarm of solar ‘bees’ are coming to western North Carolina community hubs 
Google decides which cooling system to use depending on how much water is available in a given location, according to Ben Townsend, the company’s head of infrastructure and sustainability. 
The company assesses local watersheds before and after building a data center. 
Meta’s Sarpy County data center uses a combination of evaporative and closed loop cooling. 
While data centers have typically been built in urban areas, developments have started to move further out to suburbs and rural areas as fiber optic cables and infrastructure has improved, said Dan Diorio, vice president of state policy at the Data Center Coalition. 
This expansion raises concerns for areas of Nebraska that either don’t have enough water already or whose water supply is already fully allocated. 
Most of the state’s water is used for irrigation to support the agriculture-based economy. 
With water use expected to rise due to droughts and higher temperatures from climate change, water policy and allocation are top of mind, said Crystal Powers, water extension educator at the University of Nebraska-Lincoln. 
“From a logical, common-sense perspective, we really need to stop putting industry in areas where they can’t be supported” by natural resources like water, said John Winkler, general manager of the Papio-Missouri River Natural Resource District. 
“It doesn’t make sense to put a data center in an area that’s very water-insecure to begin with.” 
Masanet and fellow researcher Jonathan Koomey said the pressure is being put on the data center industry to be more efficient and transparent. 
“I work with a lot of people in the tech industry. 
They’re pouring trillions into this industry,” Masanet said. 
“We should hold them to account and make them install the very best technologies that minimize energy and water.” 
This story was originally published by Grist with the headline Nebraska wants data centers to come clean about water usage on Jul 15, 2026. 
Article reasoning-pattern comparisonThis article: 7.1%Anila Yoganathan: 1.8%Grist: 2.2%Confirmation Bias7.1%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.8%Anchoring Bias0.0%This article: 7.9%Anila Yoganathan: 4.4%Grist: 3.0%Availability Heuristic7.9%This article: 1.9%Anila Yoganathan: 0.5%Grist: 1.0%Representativeness Heuristic1.9%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.5%Hindsight Bias0.0%This article: 4.4%Anila Yoganathan: 1.1%Grist: 1.3%Overconfidence Bias4.4%This article: 19.9%Anila Yoganathan: 10.3%Grist: 5.0%Framing Effect19.9%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.7%Loss Aversion0.0%This article: 6.0%Anila Yoganathan: 1.5%Grist: 0.5%Status Quo Bias6.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.3%Sunk Cost Effect0.0%This article: 5.0%Anila Yoganathan: 1.2%Grist: 3.1%Optimism Bias5.0%This article: 6.6%Anila Yoganathan: 1.7%Grist: 2.0%Pessimism Bias6.6%This article: 19.4%Anila Yoganathan: 8.1%Grist: 6.8%Negativity Bias19.4%This article: 4.2%Anila Yoganathan: 1.0%Grist: 1.0%Self-Serving Bias4.2%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.6%Fundamental Attribution Error0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.1%Actor-Observer Bias0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.8%In-Group Bias0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.2%Out-Group Homogeneity Bias0.0%This article: 5.3%Anila Yoganathan: 1.3%Grist: 1.0%Halo Effect5.3%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.0%Horn Effect0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.0%Dunning-Kruger Effect0.0%This article: 1.1%Anila Yoganathan: 0.3%Grist: 1.2%Recency Bias1.1%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.3%Primacy Effect0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.1%Blind-Spot Bias0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.3%Ad Hominem0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.1%Straw Man0.0%This article: 21.7%Anila Yoganathan: 6.7%Grist: 4.1%Appeal to Authority21.7%This article: 8.3%Anila Yoganathan: 2.8%Grist: 1.4%False Dilemma8.3%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.9%Slippery Slope0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.1%Circular Reasoning0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 3.9%Hasty Generalization0.0%This article: 1.8%Anila Yoganathan: 1.4%Grist: 0.1%Red Herring1.8%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.6%Bandwagon0.0%This article: 8.6%Anila Yoganathan: 3.4%Grist: 4.0%Appeal to Emotion8.6%This article: 5.0%Anila Yoganathan: 1.9%Grist: 0.7%Begging the Question5.0%This article: 5.1%Anila Yoganathan: 1.3%Grist: 3.1%Post Hoc (False Cause)5.1%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.0%Tu Quoque0.0%This article: 2.6%Anila Yoganathan: 0.7%Grist: 0.3%Burden of Proof2.6%This article: 1.4%Anila Yoganathan: 0.3%Grist: 0.3%Appeal to Nature1.4%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.3%Composition/Division0.0%This article: 2.6%Anila Yoganathan: 0.7%Grist: 2.0%Anecdotal2.6%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.0%No True Scotsman0.0%This article: 5.0%Anila Yoganathan: 1.2%Grist: 1.7%Ambiguity (Equivocation)5.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.1%Middle Ground0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.1%Personal Incredulity0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.1%Special Pleading0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.0%Genetic Fallacy0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.8%Unattributed Quote0.0%This article: 0.3%Anila Yoganathan: 0.5%Grist: 1.0%Quote-first Misdirection0.3%This article: 6.1%Anila Yoganathan: 3.4%Grist: 2.5%Biased Writer Voice6.1%This article: 12.0%Anila Yoganathan: 5.6%Grist: 1.4%Indoctrination12.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 1.0%Politically Left Leaning Bias0.0%This article: 0.0%Anila Yoganathan: 0.0%Grist: 0.1%Politically Right Leaning Bias0.0%This article: 2.4%Anila Yoganathan: 0.6%Grist: 0.7%Attempt to Sell a Product or S…2.4%

722 words analyzed.

Speakers

9speakers54%attributed speech333writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 10 words • 0.0% coverageWriter's voice • 44 words • 100.0% coverageJesse Bradley • 36 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 37 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageGoogle • 17 words • 100.0% coverageGoogle • 14 words • 0.0% coverageMeta • 31 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 2 words • 100.0% coverageEric Masanet • 11 words • 0.0% coverageEric Masanet • 32 words • 100.0% coverageWriter's voice • 13 words • 0.0% coverageBen Townsend • 29 words • 0.0% coverageGoogle • 12 words • 0.0% coverageMeta • 14 words • 0.0% coverageDan Diorio • 43 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageCrystal Powers • 34 words • 0.0% coverageJohn Winkler • 36 words • 100.0% coverageJohn Winkler • 18 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageEric Masanet • 11 words • 0.0% coverageEric Masanet • 8 words • 0.0% coverageEric Masanet • 19 words • 100.0% coverageGrist • 24 words • 0.0% coverage
Selected voice

John Winkler

100%flagged-word coverage
54 attributed words14% of attributed speech82% writer coverage
0%35.0%70.0%Indoctrination+66.7 ptsWriter: 0.0%John Winkler: 66.7%66.7%Biased Writer Voice-13.2 ptsWriter: 13.2%John Winkler: 0.0%0.0%Quote-first Misdirection-0.6 ptsWriter: 0.6%John Winkler: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.