Yakun Zhang, a newly hired assistant professor at the University of Wisconsin-Madison, is combining artificial intelligence with soil science to help farmers and land managers monitor and protect one of Earth's most undervalued resources: soil itself. Her research integrates AI, data science, sensors, and geospatial analysis to improve our understanding of soil processes and support sustainable agriculture, water management, and climate resilience.

What Makes Soil Such a Critical Climate and Agriculture Challenge?

Most people don't think much about soil, but Zhang highlights a sobering reality: it takes roughly 1,000 years to form just one inch of fertile topsoil, yet that soil can be lost within decades through erosion, deforestation, and poor land management. This means soil is effectively a nonrenewable resource on human timescales. As climate change intensifies droughts, floods, and unpredictable growing seasons, the ability to monitor and manage soil health in real time becomes increasingly critical for food security and environmental stability.

Zhang joined UW-Madison in January 2026 as part of RISE-AI, the university's technology-focused strategic hiring initiative designed to tackle major challenges through innovation. Her position reflects a growing recognition that traditional soil science alone cannot keep pace with the scale and speed of environmental change.

How Can AI and Sensors Help Monitor Soil Health?

Zhang's research program focuses on developing practical tools that use innovative sensing technologies and AI-driven approaches to improve the monitoring, prediction, and management of soil and environmental systems. Rather than relying on periodic soil samples taken by hand, these technologies enable continuous, large-scale data collection that reveals patterns invisible to the human eye.

The applications span multiple areas critical to sustainability:

• Water and Nutrient Management: AI models can predict how water and nutrients move through soil, helping farmers apply inputs more precisely and reduce waste.
• Soil Health Enhancement: Real-time monitoring allows land managers to detect early signs of degradation and intervene before damage becomes severe.
• Climate Adaptation: By understanding soil processes better, researchers can develop strategies to help agricultural systems withstand climate-related stresses like drought and flooding.
• Sustainable Agriculture Support: Farmers and policymakers gain data-driven insights to make decisions that balance productivity with environmental protection.

Zhang explained her vision for the field in her faculty profile: "The main goal of my research program is to improve the monitoring, prediction, and management of soil and environmental systems using innovative sensing technologies, AI-driven approaches, and large environmental datasets," she stated. She emphasized that her work aims to develop practical tools to support farmers, land managers, policymakers, and communities by improving soil and water management, promoting sustainable agriculture, and helping address environmental challenges through science and technology.

Zhang

Why Does This Matter Beyond the Farm?

Soil health directly influences carbon storage, water filtration, crop productivity, and ecosystem resilience. When soil degrades, it releases stored carbon into the atmosphere, worsening climate change. When soil is healthy, it acts as a carbon sink and filters water naturally, reducing the need for expensive treatment infrastructure. Yet most soil monitoring remains labor-intensive and sporadic, leaving blind spots in our understanding of how land is changing.

Zhang's approach bridges that gap by automating and scaling soil observation. AI can process data from thousands of sensors across vast areas, identifying patterns that would take human researchers years to detect manually. This speed and scale are essential as climate change accelerates soil degradation in some regions while creating new opportunities for soil restoration in others.

What Will Zhang Teach the Next Generation?

Beyond her research, Zhang is launching a new course on AI in environmental science at UW-Madison, introducing students to the applications of artificial intelligence, machine learning, and data science in environmental and agricultural research. She emphasized the importance of critical thinking and interdisciplinary collaboration, noting that many of today's environmental challenges are complex and require knowledge from multiple fields.

"I hope students understand the importance of critical thinking and interdisciplinary collaboration. Many of today's environmental challenges are complex and require knowledge from multiple fields. I also want students to recognize that strong quantitative and computational skills can greatly expand their ability to solve real-world environmental problems," Zhang explained.

Yakun Zhang, Assistant Professor of Soil and Environmental Sciences at University of Wisconsin-Madison

Her emphasis on computational skills reflects a broader shift in environmental science: the future of sustainability depends on researchers who can speak both the language of ecology and the language of data. As AI tools become more powerful and accessible, the bottleneck is no longer computing power but human expertise in asking the right questions and interpreting the results responsibly.

How Is This Part of a Larger Climate AI Movement?

Zhang's work exemplifies a growing trend of using AI to solve climate and sustainability challenges at the intersection of agriculture, water, and soil science. While much attention has focused on AI's energy consumption, her research demonstrates how AI can be deployed to reduce resource waste and improve environmental outcomes when applied thoughtfully to real-world problems like soil degradation and water scarcity.

Her hiring as part of RISE-AI signals that universities and research institutions are prioritizing the integration of advanced technology with environmental science. This approach recognizes that climate solutions will require not just policy or individual behavior change, but also smarter tools for monitoring, predicting, and managing natural systems at scale.

As soil continues to disappear faster than it forms, researchers like Zhang offer a data-driven path forward, one sensor and one AI model at a time.