Illinois scientists reveal how tile drainage transforms agroecosystems through soil oxygen

URBANA, Ill. [26th Nov. 2025] — A new study from the Agroecosystem Sustainability Center (ASC) of the University of Illinois Urbana-Champaign provides one of the most comprehensive explanation to date of how tile drainage, a common agricultural practice, enhances the functioning of agricultural landscapes. Although tile drainage has been widely studied as an important form of agricultural infrastructure, the new study built a comprehensive framework to explain why tile drainage is so effective across a wide range of outcomes. The study pinpoints soil oxygen dynamics as the critical, hidden mediator that is pivotal for drainage impacts on crop growth, soil health, and crop resilience.

The study recently published in Hydrology and Earth System Sciences demonstrates that the benefits of tile drainage extend far beyond simply removing excess water from fields. Tile drainage fundamentally alters soil hydrology by reducing soil water content, which then enhances soil oxygenation. These hydrological impacts have complex effects on soil biogeochemistry and plant biology. For example, the improved aerobic condition alleviates crop oxygen stress during wet springs, which, in turn, promotes early crop root growth. The increase in oxygen availability also stimulates microbial activity, which accelerates the decomposition of organic matter and nutrient cycling.

The research team used an advanced, process-based model called ecosys that is uniquely capable of simulating the physics of soil oxygen movement and crop oxygen uptake. After validating the model against multi-year field data, the researchers ran simulations comparing drained and undrained conditions to understand the full set of ecological changes following drainage.

According to Kaiyu Guan, the project’s principal investigator and a Levenick Endowed Professor and Director of the Agroecosystem Sustainability Center at the University of Illinois, “Previous models that do not explicitly simulate soil oxygen dynamics fail to capture the true impacts of tile drainage, making it hard to accurately predict agriculture outcomes such as yield, nutrient availability, and nutrient leaching. These outcomes and the underlying processes must be understood through the lens of soil oxygen.”

“Most models use soil water as a simple proxy for oxygen stress, but without explaining the underlying physical mechanisms that improve crop outcomes. Our work focuses on the central role of oxygen. Its availability depends on the balance between supply (oxygen diffusion through soil) and demand from roots and microbes. This allows us to provide a holistic view of how tile drainage impacts the broader agroecosystem,” said lead author Zewei Ma, a PhD student at the University of Illinois under Prof. Guan.

The authors note that while conventional tile drainage provides clear agronomic benefits, emerging practices such as controlled drainage offer a more comprehensive approach that help mitigate potential water-quality trade-offs. By adjusting outflow during different parts of the season, controlled drainage can retain more water and nutrients in the field while still improving soil oxygen dynamics when crops are most vulnerable to oxygen stress.

The key findings of the study include:

• Soil oxygen as the key controlling factor: By removing excess water, tile drainage actively oxygenates the soil. The improved aerobic environment results in a range of soil health benefits.
• Stronger root development: Improved soil oxygen levels during wet springs alleviate stress on crop roots, allowing them to respire and grow more efficiently. This leads to the development of denser and deeper root systems.
• Accelerated nutrient cycling: Higher oxygen levels stimulate microbial activity, which accelerates organic matter turnover and increases nutrient availability for crops.
• Water quality trade-off: The study also confirmed that tile drainage can lead to increased leaching of soil nitrogen into waterways, highlighting the need for paired conservation practices to protect water quality.

“This research provides a mechanistic understanding of why drainage benefits crops. It goes far beyond water management; it improves the conditions for microbes and crop roots in the soil. By reducing oxygen stress in the root zone, the plants have greater ability to establish a resilient foundation for the entire growing season,” said co-author Bin Peng, an assistant professor on agricultural water management and water quality at the Department of Crop Sciences at the University of Illinois.

Professor Guan emphasized the broader implications, saying: “As we face a future with more climate extremes, strategic water management is essential for food security. This study gives us a powerful predictive tool to assess where and how tile drainage can best serve as an adaptation strategy, not just for increased yield, but for greater long-term yield stability.” 

The researchers hope their findings will inform farmers, agricultural advisors, and policymakers on the multifaceted value of drainage management and the importance of integrating it with other practices to ensure both productivity and environmental sustainability.

The paper, “Soil oxygen dynamics: a key mediator of tile drainage impacts on coupled hydrological, biogeochemical, and crop systems,” is published in Hydrology and Earth System Sciences [DOI: 10.5194/hess-29-6393-2025]. The work was supported by the National Science Foundation, the U.S. Department of Agriculture, the Foundation for Food & Agriculture Research, and the U.S. Department of Energy.

For more information, contact:
Kaiyu Guan, Professor
Department of Natural Resources and Environmental Sciences
University of Illinois Urbana-Champaign
kaiyug@illinois.edu 

Bin Peng, Assistant Professor
Department of Crop Sciences
University of Illinois Urbana-Champaign
binpeng@illinois.edu

URBANA, Ill. — In the face of increasing global drought risk, understanding how plants respond to water stress has never been more critical. Researchers at the University of Illinois Agroecosystem Sustainability Center have delivered a pioneering synthesis that reconciles decades of differing approaches to modeling water use and dynamics in plants. The result: a unified theoretical framework and improved tools for predicting plant behavior under drought, and more informed decisions for agriculture and ecosystem management.

Transpiration, the process by which water moves from soil, through plants, and into the atmosphere, is a critical part of Earth’s water and energy cycles. It links plant physiology to weather and climate patterns and returns a significant amount of water that falls on land back to the air. During transpiration, the tiny pores in plants – stomata – release water vapor on the leaf surface and also absorb carbon dioxide to fuel photosynthesis, making transpiration a crucial indicator of plant health and productivity. 

Modeling transpiration has a long and evolving history. Scientists have historically used two broad types of models to simulate plant water stress: empirical models based on  statistical relationships between water in soil and plants, and mechanistic models based on physical laws that describe biological and biophysical processes. Early mechanistic models introduced empirical approaches, such as the Beta function, which scales transpiration in proportion to the soil water content. The supply-demand balance scheme is a more sophisticated empirical approach used in crop growth models that accounts for how easily water moves through soil and plant roots. These approaches are easy to implement and efficient, but often oversimplify plant physiology and lead to errors. Ideally, a model should be just complex enough to accurately simulate a specific environment. 

In contrast, advanced mechanistic approaches such as plant hydraulic models offer detailed simulations of water transport through plants, but require many parameters that are difficult to measure and long computation times. Until now, the relationships among these models (and the best choice for a given application) have remained unclear.

Lead author Dr. Yi Yang and colleagues, led by the project director Dr. Kaiyu Guan, have now developed a novel mathematical framework that formally connects these different approaches. The team was able to see that the simple empirical approaches are specific cases of the complex mechanistic approach. “Scientists have debated which method is the best way to capture how plants respond to drought, but what we really needed was a clear way to connect them all,” said Yang, the former Ph.D. student of Dr. Guan in the Department of Natural Resources and Environmental Sciences. “We show that we don’t have to choose between simplicity and realism. We can understand where each method fits and see that they are connected as special cases within a unified system.”

The researchers used data from three contrasting ecosystems: a humid Midwestern cropland, a semi-arid conifer forest, and an arid grassland, to show how the best choice of model depends on the specific site and conditions. Researchers were then able to see how the models respond to different environments and different plants. 

Understanding whether plant stress is caused by dry air, dry soil, or both is key. While droughts in many parts of the world are becoming more common, the Midwest U.S. often experiences ‘atmospheric drought’ (hot, dry air), even when soil moisture is still available.  “This framework helps us better simulate how plants respond when the air is dry but the soil may not be,” Yang said. “That’s crucial for predicting stress under future climate conditions.” 

In the example of U.S. corn and soy fields, the empirical models strongly overestimated transpiration during periods of atmospheric drought with normal soil moisture but dry air. In this case, detailed models that capture how plants manage internal water flow become more important for accurate predictions.

However, in consistently dry environments or for plants such as grasses with a fairly simple water transport pathway, the simpler Beta model works well. The arid grassland case study demonstrated that the more empirical models performed similarly to the complex mechanistic models, suggesting that the more sophisticated approach isn’t needed for reliable results in these settings. 

“Our contribution allows us to determine how the drought stress affects plant transpiration with fewer data and with better efficiency,” Yang said. “If you need to rely on the more complex mechanistic model, you must gather more data and likely must go to the field to measure its hydraulic parameters in order to predict the stress level. With our improved framework and understanding, we can instead estimate that stress level with satellite data in some cases, because we can remove unnecessary parameters from the equation.”

From an agricultural management perspective, more precise estimates of plant water use help farmers optimize irrigation, saving water while protecting yield. By knowing when crops are likely to suffer stress, growers can better time irrigation during critical growth stages like mid-summer, when healthy transpiration supports peak photosynthesis and grain fill.

“How to reconcile these different transpiration modeling theories was a long-standing problem of mine from my own PhD time through my early career as a professor, ” said Guan. “I am so proud that my student Yi made such a breakthrough to close this major scientific gap.” 

ASC researchers Bin Peng, Jingwen Zhang, Lisa Ainsworth, and Sheng Wang joined scientists from the University of Minnesota, Cornell University, the University of California-San Diego, University of Texas Austin and the Pacific Northwest Natural Laboratory on this project.

The project received support from an NSF CAREER award managed through the NSF Environmental Sustainability Program and USDA/NSF Cyber-Physical-System Program as well as a an annual small grant award from USGS Illinois Water Resources Center. Funding for AmeriFlux and FLUXNET data resources and core site data was provided by the U.S. Department of Energy’s Office of Science. Funded was also provided by the DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI) funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research.

The new study is titled “A Unified Framework to Reconcile Different Approaches of Modeling Transpiration Response to Water Stress: Plant Hydraulics, Supply Demand Balance, and Empirical Soil Water Stress Function” and is published in Journal of Advances for Modeling the Earth System (JAMES) [doi: 10.1029/2023MS003911]. 

Read the full article here

Kaiyu Guan has been awarded the 2025 agInnovation Research Innovation Award of Excellence for his groundbreaking work in integrating advanced computational modeling with AI methods and remote sensing to advance food security and sustainability, as well as his leadership in resilient agriculture and policy-forward research.

Kaiyu Guan, the Founding Director of the Agroecosystem Sustainability Center (ASC) and a professor of Natural Resources and Environmental Sciences at the University of Illinois, has been selected as the American Society of Agronomy (ASA) Plenary E.T. and Vam York Distinguished Lectureship at the ASA annual meeting. The international annual meeting is the largest gathering of soil, crop, and agronomic scientists in the world.

It will be presented at the annual meeting of the ASA, the Crop Science Society of America, and the Soil Science Society of America on Nov. 10-13, 2024, in San Antonio, Texas. This conference is the most important gathering for agricultural scientists in the US and globe, for exchanging and sharing ideas, solutions, and innovation from across the field of agricultural sciences.

Guan will deliver an address titled SYMFONI: The “System-of-Systems” Solution to Quantify Soil Carbon and GHG Outcomes for the U.S. Croplands. Guan is the project leader of SYMFONI, an ARPA-E SMARTFARM project, which advanced the first-of-its-kind system-level quantification of greenhouse emissions for agroecosystems from field to continental scales. His group has developed accurate and scalable quantification of soil carbon and greenhouse gas emissions for corn, soybeans, spring and winter wheat, cotton, rice, pastureland, and miscanthus fields.

Guan founded and directs ASC, which has a mission to revolutionize agricultural systems through research, collaboration, and engagement, bridging science and practice for agricultural productivity and ecosystem sustainability. He is also the Chief Scientist for the NASA Acres Program. His research group uses computational models, satellite data, field work, and artificial intelligence to address how climate and human practices affect crop productivity, water resource availability, and ecosystem functioning. Guan’s group aims to increase our society’s resilience and adaptability to maintain sustainability of ecosystem services, food security and water resources.