July 28, 2026 — The cause of water shortages and wildfires worldwide, the ongoing drought crisis demonstrates the urgent need to proactively predict when and where drought conditions will occur well before they happen. Virginia Tech experts say the artificial intelligence (AI) technology that makes this possible exists — the key is maximizing access to worldwide weather and water use data.

“AI tools are only as good as the data we can put into them,” said geography expert Craig Ramseyer. “I would argue that the input data is more important than the technology itself. The U.S. and our partners abroad must continue to invest in data collection if we are to continue our progress in mitigating drought.”

“Deep learning models excel at fusing and creating outcomes from varied data streams — satellite imagery, soil moisture sensors, crop health indicators, and weather data — to detect early drought stress patterns that are invisible to traditional statistical models,” said biological systems engineer and AI expert Feras Batarseh.

“Often the atmosphere and the land surface start leaving clues that a drought may soon begin, and those clues can be measured with satellite data and weather stations. AI can then use those data to identify patterns and forecast impending drought,” Ramseyer said. “This requires an abundance of satellite data constantly monitoring the land surface and our lower atmosphere, allowing us to ‘see’ parts of the globe where there’s no reliable data being collected on the ground.”

In the United States, the ongoing drought affects more than 100 million people. Especially in Midwestern and Southeastern states, conditions ranging from moderate to extreme threaten crops and livestock. Detecting the weather patterns that lead to drought makes advance irrigation and conservation planning possible, and AI can assist with that.

“Data has become as critical to water security as reservoirs,” said Batarseh. “By learning optimal irrigation schedules, reservoir release strategies, and crop allocation policies, AI agents can use trial-and-error simulations to balance competing objectives such as water conservation, yield stability, and energy use, even as weather conditions change.”

AI can complement traditional weather forecasting. “Right now, AI models are used alongside our traditional physics-based, mathematical weather models because AI models generally have higher error predicting our most extreme events,” Ramseyer said. “Researchers use AI because it’s fast and can find patterns in any data you provide it; thus, it’s of great assistance with specific research questions.”

About Batarseh

Feras Batarseh directs the Artificial Intelligence Assurance and Applications (A3) Lab at Virginia Tech. An associate professor of biological systems engineering and an affiliate with the Commonwealth Cyber Initiative, his research spans the areas of artificial intelligence and cyberbiosecurity for water systems and smart agriculture. The team he leads develops AI applications and assurance algorithms to address persisting water security and agricultural public policy challenges.

About Ramseyer

Craig Ramseyer, associate professor in Virginia Tech College of Natural Resources and Environment Department of Geography, leverages AI models to analyze how climate change is changing drought and flooding. Other research includes weather impacts on football player mortality and moisture impacts on Greenland ice melt, and a recent study of the phenomenon of “flash drought,” drought that sets in within days rather than weeks, in Puerto Rico.