Developing a Climate-Smart Practice Optimization Tool for Sustainable Agriculture in the US

Three images of trees, plants and agriculture. The middle image says Numerical Tools for Climate Smart Agriculture


This VIP aims to develop a climate-smart practices optimization tool for enhancing the climate resilience of agriculture in the US.

What are climate-smart agricultural practices?

Practices that could intensify crop yields by:

  • Optimizing nutrient use efficiency (NUE)
  • Optimizing water use efficiency (WUE)
  • Minimizing greenhouse gasses (GHG) emissions

We will integrate observations with artificial intelligence (AI) and process-based models to investigate the question:

How can we optimize agricultural management practices (e.g., biochar addition, fertilization, irrigation, planting, and harvest) to achieve the “Climate-smart” objective?

This project involves two types of activities for undergraduate students:

  • Type 1 (Data-dominated work) focuses on agricultural practice-related data mining, statistical analysis, optimization, and visualization.
  • Type 2 (model-dominated work) focuses on model parameters optimization, and AI model training and testing.

As a student, you will be able to choose which path you want to follow based on what you enjoy, and what you're studying. If you're into data, experiments, and creating visuals, Type 1 might be your thing. If you love working with computers, software, and using AI to solve problems, then Type 2 may be where you'd thrive. 

With either type of activity, you'll be learning about agricultural practices while making a real impact on future climate-smart agriculture. 

Issues Involved or Addressed

  • Climate resilience assessment and optimization
  • Climate-smart agriculture and ecosystem management
  • Water cycle, energy balance, and carbon cycle
  • Soil carbon sequestration and nutrient availability
  • Water quantity and quality
  • Model parameter optimization
  • AI model training and testing

Methods and Tech

  • Data mining, collection, and organization (Microsoft Excel, etc.)
  • Statistical data analysis, interpretation, and visualization (Python/MATLAB/R)
  • Spatial data analysis and visualization
  • Artificial intelligence and modeling (Python/Fortran)
  • Science and interdisciplinary communication

Academic Majors of Interest

Our VIP team is open to all majors, with particular interest in the students with any of the following backgrounds:

  • Hydrology and Atmospheric Sciences
  • Ecology & Evolutionary Biology
  • Environmental Science
  • Natural Resources
  • Computer Science
  • Mathematics and/or Statistics & Data Sciences
  • Crop Sciences
  • Geosciences

Preferred Interests and Preparation


  • Basic ability to conduct literature reviews, gather relevant research materials and synthesize information
  • Basic ability to use statistical analysis tools, such as Excel, R, MATLAB, or Python
  • Preferred: Computer programming (e.g., Python/Fortran) or AI/ML model experience
  • Preferred: Spatial data analysis and mapping experiences, such as GIS applications, NETCDF data analysis and visualization


  • A genuine interest in addressing climate change and its impact on agriculture
  • Enjoys interdisciplinary research and collaborative work environments
  • Reliability and accountability in handing research tasks and data
  • Commitment to research excellence and the ability to meet project deadlines
  • Careful and meticulous approach to data analysis and research tasks

Application Process

If you are excited about our VIP research in developing a climate-smart agriculture practices tool, we encourage you to apply.Join us in our mission to create a more climate-resilient future for agriculture in the United States. Together, we can make a difference!

If you are interested in joining this VIP team for class credit, contact Dr. Song by completing a VIP Interest Form and selecting the team "Developing a Climate-Smart Practice Optimization Tool for Sustainable Agriculture in the US."

If you are interested in a Federal Work-Study position with this team, please submit 1) your resume/CV, and 2) a one-page cover letter detailing your interest and/or relevant experience to Dr. Yang Song (

Application Deadline: the position will be closed by Dec 31, 2023, or until we find sufficient candidates.

Team Advisor