Title: Agricultural Research Panel: A Perspective of Research and Challenges in the Soil & Water Section
In the department of Agricultural and Biological Engineering (ABE), the Soil and Water Resources Engineering (SWRE) section leads federal and state-funded research projects that are aimed at mitigating the impacts of excess pollutants (e.g., nutrients, sediments, and pathogens) while supporting decision-making processes across physical, social and economic scales. Such research is critical for sustainable agro-production systems.
Dr. Chu's research seeks to understand the dynamics between watersheds and the ecosystem under climate and land-use changes. Her research's overarching goal is to find the zone of intersection where productivity, social relevance, and environmental soundness are optimized to achieve a sustainable agro-production system across competing scales. She is the director of the Watershed-Ecosystem Research Laboratory.
Dr. Bhattarai’s research seeks to find various ways to clean polluted waters. The overall goal of our research group is to develop sustainable engineering solutions to improve water quality and crop production. Our group uses laboratory and field experiments, along with computer simulation models, to investigate how to balance water quality, nutrient management, and yield goals for sustainable water resources and agricultural systems.
Dr. Davidson’s research program focuses on improving and maintaining surface water systems by reducing the transport of nutrients, pathogens, and pesticides from agricultural and urban systems to waterways. He works with stakeholders to develop solutions that protect the quality of our water resources while maintaining efficient operations. He works extensively at the intersection of engineering and biology/chemistry, as these disciplines are all valuable for addressing water quality challenges.
Dr. Guzman's research goals encompass an improving understanding of surface and groundwater interactions, including transport phenomena under climate and land-use changing scenarios. In this context, Dr. Guzman uses intensive data and modeling approaches to assess and account processes and uncertainty, develop new codes, algorithms, and computing-intensive and data-intensive applications to support his research, including integrating big data, data analytics, and statistical modeling.
