Predicting Drought: Using AI to Map Water Scarcity

By: Daniel R. (Age 17, Phoenix, AZ)

Growing up in Arizona, drought was always part of the background, something people talked about in the news but not something I truly understood. Every summer, when the ground cracked and the desert turned from gold to gray, I wondered how scientists could predict when the next dry season would hit or how severe it would be.

That question led me to my research project, using artificial intelligence to predict drought risk from satellite data. I did not have a lab or a research team, only open data, free software tools, and a determination to see what patterns I could uncover.

Using NASA’s Earth observation datasets, I collected information on surface temperature, vegetation cover, and soil moisture across different regions of the Southwest. My goal was to train a simple machine learning model that could identify when conditions suggested the early stages of drought.

At first, the process was overwhelming. The data was messy, full of gaps and outliers, and the model sometimes misread cloudy days as changes in moisture. With guidance from my mentor, I learned how to clean and normalize the data, test different model types, and visualize results on a heat map that showed where drought risk was increasing.

What surprised me most was how accessible these tools have become. With a laptop and free software libraries like TensorFlow and Google Earth Engine, I could analyze patterns that once required supercomputers. My model was not perfect, but it demonstrated how open technology can empower students, researchers, and small communities to prepare for environmental change.

One of my mentor’s questions stayed with me: “How would this help people on the ground?” That pushed me to think beyond prediction and focus on communication. I started designing a simple interface that local water agencies or students could use to visualize drought probability in real time. The idea was to make data less intimidating and more useful.

“AI can help us see patterns before we feel them. That is the kind of foresight we need.”

Working on this project made me realize that AI is not only about intelligence, it is also about awareness. It is a way of paying attention to the world before crisis hits. Predicting drought is only the beginning. The real challenge is how we use that foresight to protect people, preserve resources, and plan responsibly for a changing planet.