CAREER: CAS-Climate: Assessing Manure Management and Climate Emissions on Animal Feeding Operations via Satellite Remote Sensing

About This Grant

How animal farms manage manure significantly affects environmental sustainability and public health. Across the U.S., farms primarily use lagoon systems to store and treat manure. Improving lagoon water quality and reducing greenhouse gas emissions are critical challenges facing the animal agriculture industry. This project combines advanced satellite remote sensing, artificial intelligence, and field-based data collection to better understand the drivers of lagoon conditions and the effectiveness of manure management practices. The outcomes are targeted to support sustainable manure management strategies, reduce environmental impacts, and optimize nutrient recycling. Additionally, the project will inspire the next generation of agricultural professionals through hands-on research opportunities and will provide evidence-based management recommendations to stakeholders. Promoting sustainable manure management practices requires a comprehensive evaluation of lagoon performance on a regional scale, addressing the current gaps in knowledge due to the variability of lagoon systems across farms and seasons. This project leverages satellite imagery, machine learning, and metagenomics to analyze lagoon conditions and greenhouse gas emissions across diverse climates and farming systems. By constructing a robust database of lagoon characteristics, (1) the study aims to quantify variability in water quality and emissions from lagoons at the state level, (2) assess historical trends in lagoon performance over the past two decades, and (3) identify the key biological, chemical, and physical factors influencing lagoon dynamics. The findings will support the development of decision-support tools for farmers and policymakers, enabling actionable solutions such as nutrient redistribution strategies and optimized lagoon designs and practices. Beyond advancing agriculture and engineering, the project will also provide interdisciplinary research opportunities that train students and contribute to workforce development. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.