Natural Climate Solutions: When and where do they work for farmers and the climate?
Xian Wang
Faculty Mentor
Xian Wang (O'Neill School of Public & Environmental Affairs)
Project Description
Agricultural conservation practices like no-till farming and cover cropping are widely encouraged for their potential to help reduce climate change. These practices can make farm fields reflect more sunlight (increasing surface albedo) and store more carbon in soil and plants—both of which can reduce greenhouse gas impacts. However, while these practices are good for the climate, their impact on crop yields is less clear, especially across different weather conditions. This project investigates how no-till and cover cropping affect both crop productivity and climate outcomes across the U.S. Midwest, a region critical for national food production and increasingly vulnerable to climate extremes. We focus on Indiana as a case study and extend our analysis to surrounding states with similar farming systems and climate trends. By combining detailed conservation practice data (such as records of where and when no-till or cover crops were used) with satellite-based remote sensing data, we are able to track changes in yield and environmental benefits at the field level over multiple years. We compare the same fields during years when conservation practices were used versus years when they weren’t, which helps us isolate the true effects of these practices. Our initial findings show a trade-off: No-till provides clear climate benefits but can reduce yields, especially during dry seasons or in drier regions. In wetter areas or years, both yields and climate benefits from no-till tend to drop, possibly due to too much soil moisture. Cover cropping consistently improves climate outcomes but is also linked to short-term yield losses. However, the longer these practices are used, the more likely they are to reduce yield penalties—likely due to improved soil health. This project highlights the need for region-specific strategies. What works in one part of the Midwest may not work as well in another. Our goal is to help farmers, researchers, and policymakers develop more effective conservation plans that protect both productivity and the climate. By identifying where and when no-till and cover cropping are most beneficial, we can better support resilient and sustainable agriculture across the Midwest.
Technology or Computational Component
In this project, we use computer tools and satellite data to study how farming practices like no-till and cover cropping affect crop yields and climate across the Midwest. We work with two main types of data: Satellite images that show what’s happening on the ground—like how green the crops are, how much sunlight the land reflects, and how wet the soil might be. Field management records that tell us where and when farmers used no-till or cover crops. To handle this large amount of information, we use easy-to-learn tools such as: Google Earth Engine (GEE): A powerful website where we can look at satellite images over time. Python: A beginner-friendly programming language that helps us organize and analyze the data. Maps and GIS software: To match the satellite images with real field locations.