One year after the Trump administration launched its tariff offensive against more than 180 countries, Latin America presents a mixed picture: some economies lost competitiveness in the U.S. market, while others redirected exports or negotiated agreements to cushion the blow.
Every chip fabricated in a semiconductor plant needs ultrapure water. Most nuclear reactors need water as a coolant and neutron moderator. Every artificial intelligence (AI) data center drinks between 1 million and 5 million gallons of water a day, with thirst often peaking during drought.
Water runs through every technology priority the United States has named, yet the word does not appear once in “Launching the Genesis Mission,” an executive order (EO) released in November 2025. As described in the EO, the Genesis Mission is a “dedicated, coordinated national effort to unleash a new age of AI-accelerated innovation and discovery that can solve the most challenging problems of this century.”
Led by the Department of Energy (DOE), the initiative aims to build an integrated AI framework that would harness federal scientific datasets to accelerate breakthroughs in advanced manufacturing, biotechnology, critical materials, nuclear fission and fusion energy, quantum information science, and semiconductor development. The scope of the mission is comparable to that of the Manhattan Project.
Since the announcement, the DOE has listed “Predicting U.S. Water for Energy” among its 26 Genesis Mission Science and Technology Challenges. The project is also soliciting proposals in three water-related focus areas.
This framework provides a foothold for hydrology in the Genesis Mission, but it is scoped narrowly around water as a supply variable for energy production.
In reality, water is a crosscutting constraint that will help determine whether the mission’s priorities translate into deployable outcomes. The hydrology community now has a seat at the table, and if it moves first and positions water security as one of the “most challenging problems of this century,” the Genesis Mission can become the sandbox in which AI reshapes how the country measures, models, and manages water.
Making this happen will require that the DOE and the Office of Science and Technology Policy charter a hydrology workstream inside the Genesis Mission, with interagency delivery involving the U.S. Geological Survey (USGS), NOAA, the Bureau of Reclamation, the EPA, and partners at state, regional, and community levels. Here is what we think that workstream should look like:
A water-centric Genesis Mission architecture supports seven hydrological components that both feed into and receive decisions from the Genesis AI platform. Each component maps to a section of this article. Credit: Amobichukwu C. Amanambu. Click image for larger version.
While the existing challenges reflect some of these components, others will require coordinated effort from the hydrology community to bring into the Genesis Mission’s scope.
Build the Water Corpus Genesis Will Need
The Genesis Mission EO instructs the DOE to create an American Science and Security Platform to provide the public, scientists, agencies, and policymakers access to crucial scientific datasets.
The good news is that accessible water data systems already exist across several federal agencies and academic research centers. The USGS National Water Information System tracks real-time and historical water quality and use across the country. NASA’s Earth Science Data Systems Program provides open access to Earth science observations. NOAA’s National Water Center, the first federal facility dedicated to national water resource forecasting, operates the National Water Model, which continuously forecasts flows on 2.7 million stream reaches across the continental United States. The Catchment Attributes and Meteorology for Large-Sample Studies (CAMELS) dataset, currently hosted by the National Center for Atmospheric Research, provides data tailored for hydrological research on hundreds of river basins, and the Caravan framework pulls together multiple large-sample meteorological and hydrological datasets at a global scale.
What is missing is a unified, AI-ready repository that brings federal, state, and community data together.
What is missing is a unified, AI-ready repository that brings federal, state, and community data together. Building one is hard. Water data are fragmented, inconsistent, and often entirely absent. Consistent, reliable data for groundwater, withdrawals, reservoir operations, and water quality are especially difficult to obtain.
Local resistance to sharing data is real. In Texas, for example, landowners hold private property rights over groundwater and have opposed metering and reporting requirements imposed by groundwater conservation districts. In California, agricultural well owners fought metering mandates for years before the Sustainable Groundwater Management Act compelled local agencies to begin tracking withdrawals. Tribal nations face a different concern: Water data collected on Indigenous lands has been misrepresented in federal datasets that were modeled without accounting for Indian country, leading many nations to restrict access to their data as an exercise of sovereignty.
Practical steps toward building a unified AI-ready repository include tiered access and licensing for different stakeholders, clear provenance tracking for all data reported, financial and educational incentives for stakeholders for reporting, and targeted gap filling. Where measurements are missing, AI can fuse remote sensing with gauged records and operational logs—but only if the results carry honest uncertainty estimates tied to real decisions.
Get the corpus right, and it will outlive any single program name. It becomes infrastructure the country can lean on.
Develop Shared Hydrologic Foundation Models
The Genesis Mission EO directs the DOE to provide “domain-specific foundation models across the range of scientific domains covered.”
Hydrology has a head start. Long short-term memory (LSTM) networks are a key type of neural network designed to last thousands of time steps. Hydrology LSTMs trained on CAMELS data have already matched traditional conceptual models for daily streamflow discharge prediction. Open-source Neural Hydrology tools serve as baselines for regional runoff prediction. These predictions may serve as precursors to the foundation models the Genesis Mission envisions and building blocks from which they could be developed.
The process of scaling up these tools is not straightforward, however. A hydrologic investigation of snowmelt-driven streams in Colorado will not require the same spatiotemporal data as tile-drained fields in Iowa, for example. A hydrology-specific foundation model must take nuanced requirements into consideration and provide a clear path for managing and exploiting a variety of datasets.
Google’s Flood Hub shows what is possible: Its AI-enabled flood forecasts now cover more than 80 countries. However, Flood Hub’s core model code and trained weights remain proprietary, meaning researchers can use the forecasts but cannot rebuild or adapt the underlying models. Genesis, if well positioned, can fill that accessibility gap by producing foundation models for water that are reusable, reliable, and openly governed.
Build a National Water Digital Twin
The EO prescribes an integrated AI platform combining foundation models with simulation tools to stimulate AI-enabled innovations.
That architecture is exactly what a digital twin requires. Europe’s Destination Earth initiative is already building digital twins for weather extremes and nonstationary conditions on the Large Unified Modern Infrastructure (LUMI) supercomputer. The United Nations–led AI for Good initiative has prioritized water applications, warning that fragmented national efforts risk duplicating work.
If the United States aims for global strategic leadership in AI-accelerated science, water infrastructure cannot be an afterthought.
A water digital twin earns its keep when it makes the consequences of choices visible, in terms of flows, levels, temperatures, and risks to people and ecosystems.
Rather than starting from scratch, a water-centric Genesis Mission would unite existing federal models—the National Water Model, reservoir simulators, and groundwater codes—in a single digital twin. AI can become the thread that stitches them together, correcting biases and providing numerical solvers to enforce mass and energy balance.
What should this twin actually do? Help a dam operator decide whether to release water ahead of a storm. Tell planners where a new data center can draw cooling water without drying up a stream. Flag which coastal defenses will fail first under rising seas.
A water digital twin earns its keep when it makes the consequences of choices visible, in terms of flows, levels, temperatures, and risks to people and ecosystems.
Turn Basins into AI Test Beds
The Genesis Mission promotes AI-directed experimentation and directs the DOE to keep a record of robotic laboratories and production facilities in which such experimentation could be conducted. Hydrological field sites belong in that inventory. The National Ecological Observatory Network already operates 81 sites with standardized measurements of meteorology, surface water, groundwater, and biodiversity. The Critical Zone Collaborative Network instruments catchments to track water-soil-vegetation interactions over decades.
Formalizing these networks as AI test beds would link field observations back into the water digital twin so that experiments and models continually sharpen each other. Imagine mobile sensors steered by AI agents during a storm or aquifer recharge experiments designed by algorithms and verified in real time. That feedback loop is what separates a useful model from a decorative one.
Expand Water Challenges on the Genesis Mission List
The Exchange and What’s at Stake
Allowing water security to flow through the diverse components of the Genesis Mission would benefit both the policies championed by the mission itself and the hydrology community.
The Genesis Mission gets real-world, noisy test beds where AI proves value beyond benchmarks, a domain to stress test climate and infrastructure investments, and scientists trained in both AI and the stubborn realities of rivers, aquifers, and pipes.
Hydrology gets resources for shared data infrastructure, foundation models and instrumented basins no single lab can support, a seat when rules for AI and national scientific infrastructure are negotiated, and a chance to reset practices around openness, collaboration, and equity.
Earlier this year, the DOE released 26 Genesis Mission Science and Technology Challenges, and “Predicting U.S. Water for Energy” was among them. The accompanying funding call (DE-FOA-0003612) solicits proposals on cloud microphysics, coupled surface water–groundwater modeling, and seasonal to multiyear prediction, all framed around energy needs and flood resilience.
These inclusions are a significant win for a hydrology component to Genesis, but several urgent challenges sit outside their scope. Can AI close the gap between a flood forecast issued 12 hours out and the 48 hours emergency managers actually need? Can it map compound extremes, in which drought, heat, and infrastructure failure collide in the same week? Can it redesign monitoring networks so that coverage follows risk rather than where gauges happened to be installed a century ago? Integrating energy and water systems is equally urgent: Floods have caused 80% of major U.S. grid outages since 2000, while drought-driven water stress curtails cooling at thermoelectric plants and reduces hydropower output, exposing how deeply energy infrastructure depends on hydrologic extremes.
The water footprint of new AI infrastructure deserves a place on that list. A separate executive order (14318, “Accelerating Federal Permitting of Data Center Infrastructure”) is already fast-tracking expansion of data center construction, and a single hyperscale facility can consume 1 million to 5 million gallons of water daily. Emerging research shows how withdrawals at that scale can push streams below ecological thresholds during low flows.
Make Hydrology the Conscience of AI Governance
The EO directs the DOE to set data access rules and clarify policies for ownership, licensing, trade secret protections, and commercialization of products and tools associated with it.
Three principles should anchor such policies for AI use in water security.
First, Indigenous and community data rights must be embedded in every major AI water security effort, in line with the collective benefit, authority to control, responsibility, and ethics (CARE) principles for Indigenous data governance.
Second, AI’s own water footprint, through electricity generation and cooling, must be treated as a design constraint. Transparent reporting, stress-based siting, and efficiency targets will prevent hydrology in Genesis from being self-defeating.
Third, the DOE should define what failure looks like. Missing a flood crest portends loss of lives and livelihoods and breaches of treaties. Accountability standards must be measurable, and they must ask not just how accurate the forecast was on average, but who bore the cost when it was wrong.
A single executive order will not solve the country’s water security problems, and a single challenge topic will not either.
But the Genesis Mission has provided a seat at a table that did not exist 6 months ago. Whether the hydrology community treats it as a ceiling or a foundation depends on what happens next. Europe’s Destination Earth and the United Nations’ AI for Good water initiatives are already moving.
American hydrology now has a seat at the table. We should take it.
Kratzert, F., et al. (2019), Toward improved predictions in ungauged basins: Exploiting the power of machine learning, Water Resour. Res., 55, 11,344–11,354, https://doi.org/10.1029/2019WR026065.
Xiao, T., et al. (2025), Environmental impact and net-zero pathways for sustainable artificial intelligence servers in the USA, Nat. Sustainability, 8, 1,541–1,553, https://doi.org/10.1038/s41893-025-01681-y.
Zhang, L., et al. (2025), Foundation models as assistive tools in hydrometeorology: Opportunities, challenges, and perspectives, Water Resour. Res., 61, e2024WR039553, https://doi.org/10.1029/2024WR039553.
Author Information
Amobichukwu C. Amanambu (acamanambu@ua.edu), Department of Geography and the Environment, The University of Alabama, Tuscaloosa; and Jonathan Frame (jmframe@ua.edu), Department of Geological Sciences, The University of Alabama, Tuscaloosa
Citation: Amanambu, A. C., and J. Frame (2026), The Genesis Mission needs hydrology: Here’s how to incorporate it, Eos, 107, https://doi.org/10.1029/2026EO260131. Published on 28 April 2026.
This article does not represent the opinion of AGU, Eos, or any of its affiliates. It is solely the opinion of the author(s).
China is using economic leverage to dominate the global supply chain for medicines, and the U.S. must take action to protect its leadership in the biomedical industry by strengthening regulatory frameworks and investing in domestic infrastructure.
WASHINGTON, June 6 — The United States announced Friday its approval of a US$1.98 billion (RM7.98 billion) arms sale to Kuwait, one of the Gulf countries hit by Iranian strikes during the Middle East war.
In a statement, the US State Department said it would allow purchases of counter-drone technology from defence company Anduril, which was founded by a supporter of President Donald Trump.
“This proposed sale will support the foreign policy and national security objectives of the United States by improving the security of a major non-Nato ally that has been an important force for political stability and economic progress in the Middle East,” the statement said.
Earlier this week, Kuwait officials “condemned Iranian aggression” when a drone strike on its international airport killed one person and injured 63 others.
Tehran denied involvement in the attack, saying it was “an error in the American Patriot systems,” referring to a US anti-missile battery.
The attacks came despite the April 8 ceasefire that paused the war sparked by the February 28 US-Israeli bombing of Iran, and has largely held despite sporadic exchanges of fire. — AFP
Hotter, drier conditions in the western United States have led to a rise in wildfire activity that has damaged or destroyed infrastructure, natural ecosystems, and entire towns across the region. As fires grow larger and more destructive, the cost of managing them rises as well.
Fire management agencies in the United States have been feeling the pressure. Between 2014 and 2023, fire management agencies across all levels of government experienced a 131% increase in total area burned and a 268% increase in total fire spending adjusted for inflation compared to the period between 1985 and 1994.
Today, federal agencies like the Department of the Interior (DOI) and the U.S. Department of Agriculture Forest Service (USFS) continue to invest in aiding states and managing hazardous fuel growth on public land, as well as suppressing active fires. Policymakers and federal agencies alike must decide how to manage limited budgets while protecting people, property, and natural resources.
Prestemon et al. built statistical models based on historical data to examine the potential increase in spending by the DOI and the USFS between now and 2100. Their models link wildfire activity to climate variables such as temperature and water vapor deficit and then connect fire activity to suppression costs. To capture a range of possible future conditions on federal lands, the study predicts 10 fire and suppression spending scenarios by applying five different climate models to two different warming pathways (the moderate Representative Concentration Pathways (RCP) 4.5 scenario and the high-emissions RCP 8.5 scenario).
The results varied by region and scenario, but each of the 10 scenarios suggested a rise in area burned as well as inflation-adjusted fire suppression spending, with higher fire activity translating to higher costs. Projected changes in DOI and USFS land burned increased 80% by mid-century and 208% by late century.
By the middle of the century, both agencies are projected to see spending increases: about 0.65% per year for DOI spending and about 0.87% per year for USFS spending from 2020 to 2100. Although uncertainty increased with time and outcomes varied across climate models and warming pathways, the largest increases in both cost and wildfire activity were consistently projected for the northwestern United States. (Earth’s Future, https://doi.org/10.1029/2025EF007985, 2026).
Citation: Owen, R. (2026), As wildfires increase in the West, so does suppression spending, Eos, 107, https://doi.org/10.1029/2026EO260187. Published on 10 June 2026.
Research & Developments is a blog for brief updates that provide context for the flurry of news regarding law and policy changes that impact science and scientists today.
More U.S. scientists are running for state and federal office in the U.S. midterm elections than ever before, Nature reports. Scientist-candidates represent an array of parties, although most profiled in Nature identify as Democrats.
314 Action, an organization focused on getting Democrats with scientific backgrounds elected to public office, offers financial support and training to candidates who apply for it. This year, the organization told Nature, they’ve received nearly three times as many applications as usual.
Sam Wang, a neuroscientist at Princeton and director of the Princeton Gerrymandering Project, is running to represent New Jersey’s 12th Congressional District.
“Usually, scientists stick with a specialized field,” Wang, a Democrat, wrote in an opinion for The Daily Princetonian. “However, I am deeply unhappy with how unequally power is divided in our society. So I have used my statistical abilities to level one part of democracy’s playing field: by repairing unfair elections.”
Why Now?
This year, Democratic candidates appear to be motivated by cuts to federal science programs, grants, and agencies, Nature reports, while Republican candidates like Jeff Wilson, who is running to represent the 13th district of Illinois, cite the pursuit of energy independence. Third-party scientist-candidates have also run, and scientists are entering local and municipal arenas, too.
Specifically, with the recent repeal of the Endangerment Finding, loosened restrictions on pollution, and plans to break up the National Center for Atmospheric Research, some candidates and their supporters think science needs a more prominent position in public policy.
The rise in scientist candidates may also be part of an ongoing trend. More than 200 STEM professionals ran for office in the 2024 election, as Eos reported in October 2024.
“There are a lot of people who believe that science can help us live better lives and that science really does need to be front and center when we’re making public policy,” Jess Phoenix, a volcanologist, science advocate, and former Democratic candidate for the U.S. House of Representatives told Eos at the time.
In March, thousands of people attended Stand Up for Science rallies across the country to protest the misuse of science in federal policy and extensive staffing and funding cuts to scientific agencies. Since President Trump took office in 2025, more than 10,000 PhD-level scientists have left the federal workforce, Science reported in January.
Pew research data shows that public trust in scientists has declined since the COVID-19 pandemic, but it has seen modest improvements since 2023. The latest poll, released in January, found that 77% of adults in the United States have a great deal or a fair amount of confidence in scientists to act in the public’s best interest, compared to 73% in 2023. The percentage is consistently higher among Democrats than Republicans: 90% versus 65%, in 2026. In contrast, only 27% of respondents reported at least a fair amount of confidence in elected officials.
“The last thing I want [is] to become a politician,” wrote one Redditor in response to the Nature story. “But at this rate I may not have a choice if current politicians keep screwing it up.”
These updates are made possible through information from the scientific community. Do you have a story about how changes in law or policy are affecting scientists or research? Send us a tip at eos@agu.org.
A warm, dry spring has set the stage for above-average significant wildland fire risk across much of the southern and western United States this summer, and no part of the United States will have below-average fire potential through the end of August.
“It’s not necessarily a foregone conclusion that we’re going to have a really busy season, but everything is pointing that way.”
These predictions are part of a 4-month outlook produced monthly by the National Interagency Fire Center (NIFC), a group of wildland fire experts from eight federal agencies that coordinates wildland fire resources across the country.
The most recent outlook, published 1 May, projects the likelihood of significant fires (defined as those that require an NIFC response) from May to August using long-term forecasts from NOAA’s Climate Prediction Center, current precipitation and drought conditions, and an assessment of the fuels available in different regions (like grasses, brush, and timber).
This year, 1,848,210 acres across the country have already burned—nearly twice the annual average over the past 10 years.
“It’s not necessarily a foregone conclusion that we’re going to have a really busy season, but everything is pointing that way,” said Jim Wallmann, a meteorologist for the U.S. Forest Service at the NIFC and one of the outlook’s authors.
Significant wildland fire potential will be elevated across much of the West and Southeast this summer. Click image for larger version. Credit: National Interagency Coordination Center, Public Domain
Drought in the West
In the West, wildfire season typically peaks in late summer. This most recent outlook predicts an above-average significant fire potential for much of the West as the season peaks.
In May, the above-average risk is concentrated in eastern Arizona and western New Mexico, though that risk fades to normal by August as the Southwest’s monsoon season begins. In June, the above-average risk extends to western Colorado and parts of the Pacific Northwest. In July and August, that risk covers much of the Northwest, including Utah, Idaho, Oregon, Washington, and Northern California.
Above-average spring temperatures and a far-below-normal snowpack across the West are contributing to the elevated risk in Washington, Oregon, Idaho, and Northern California, in particular. Many river basins across the West contain less than 20% of their normal amount of snow, and some are already snow-free at all observed locations due to melting caused by warm temperatures in March.
As of May, many river basins in the West have a snow water equivalent—the amount of water held in their current snowpack—that is less than 50% (in red) of the 1991–2020 average level. Credit: USDA Natural Resources Conservation Service, Public Domain
“The snowpack being lower this time of year, and melting out, affects the soil moisture throughout the rest of the summer, which then affects the fuel moistures,” said Craig Clements, a meteorologist at San Jose State University’s Fire Weather Research Laboratory who was not involved in the outlook. Early snowmelt also uncovers fuels, like pine needles and leaf litter, that would typically be under snow, exposing them to the air to dry and catch fire.
Southern California and the Sierra Nevada mountain range, though, remain at an average significant fire risk throughout the summer, as a result of higher-than-average precipitation earlier in the year.
The Southeast and Beyond
Fire risk will also be elevated in the Southeast this summer. Florida, for example, remains at an above-average significant fire potential through the end of August. Southern Georgia, Mississippi, Louisiana, Arkansas, and the eastern halves of Virginia, North Carolina, and South Carolina will also have above-average significant fire potential.
The above-average risk is fueled, in part, by a worsening drought affecting the Southeast alongside the drought in the West. As of 1 May, nearly 63% of the country was experiencing drought, and 19% of the country was experiencing extreme or exceptional drought, according to the U.S. Drought Monitor.
The Midwest and the Northeast will remain at an average significant fire potential from May to August, though northwestern Minnesota faces an above-average potential in May.
No place in the United States is projected to have a below-average significant fire potential through the end of August.
Preparing Amid Uncertainty
A developing El Niño—a climate phenomenon that affects heat storage in the ocean—could alter the fire risk projections. Scientists expect that a strong El Niño could lead to a below-normal hurricane season, worsening drought in the Southeast. In the Pacific, a strong El Niño could intensify the hurricane season, which may lower wildfire risk.
However, a stronger El Niño could drive more lightning strikes in the Sierra Nevada, which could increase fire risk there, Clements said. In 2020, for example—a strong El Niño year—Hurricane Elida in the Pacific contributed to a lightning outbreak that supercharged wildfires in the West.
“We’re still not sure exactly how [El Niño] is going to impact the season.”
“We’re still not sure exactly how [El Niño] is going to impact the season,” Wallmann said. As late summer approaches, meteorologists will better understand how El Niño will develop and affect wildfire risk.
Weather patterns can change, and day-to-day conditions still play a role in fire occurrence. “If the weather shifts, or we get a really big heat wave, it can modify [the forecast]. Or if it remains relatively moderate, that might lessen the fire danger,” Clements said. “We’ll just have to see how the weather plays out.”
Wallmann and Clements emphasized that those living in areas with elevated fire risk should be aware of their surroundings and think ahead about where they might go for safety should a wildfire occur. “Having that situational awareness ahead of time can help you make better decisions,” Wallmann said.
Citation: van Deelen, G. (2026), Most of the U.S. West will face above-normal wildfire risk this summer, Eos, 107, https://doi.org/10.1029/2026EO260145. Published on 11 May 2026.
Please be aware... Photos are purely for entertainment. I am no expert. Titles are from recognition - what I was told - or a quick search. Polite comments or corrections are welcome.
Login
One year after the Trump administration launched its tariff offensive against more than 180 countries, Latin America presents a mixed picture: some economies lost competitiveness in the U.S. market, while others redirected exports or negotiated agreements to cushion the blow.
