Systems Modeling

Systems Modeling

Our Theme: 

Systems modeling provides an understanding of agricultural systems and the way they influence and are influenced by broader aspects such as other sectors, resource availability and management, human behavior, and the institutional/regulatory context within which they function. It supports agricultural decision making and management at various spatial and temporal scales. Yield assessment, production practices, resource use, environmental footprints, and policies are enhanced by models interacting with remote sensing and other digital data sources. Focus areas for model development and applications include the following.  

  • Development and application of process-oriented dynamic models (cropping systems, hydrology, and environmental impact)
  • Development and application of data-driven empirical/ machine-learning based models 
  • Data assimilation and AI framework development to integrate models with digital data sources such as satellite imagery, observational networks and forecasts
  • Model development and application for field-scale and regional-scale decision support. Multi-scale characterization of systems and their interconnectedness
  • Food, Water, Energy interactions in coupled systems
  • Integrating economics and institutions as critical components of the systems

Ongoing Research Projects/Initiatives:

  • Technology for trade: Improving water use and allocation efficiency in agriculture and beyond  
  • Decision support for managing climate related risks in tree fruit and grapes 
    • Through multiple projects, we are exploring multiple aspects related to climate related risks in perennial cropping systems: sunburn risk in apples, honeybee pollination management, cold damage to grapevine, and codling moth pest pressures.
  • Analogs as way to communicate climate change risks and facilitate management alternatives (USDA ERME, USDA Northwest Climate Hub, USGS, USDA NIFA)
    • As part of multiple projects, we are exploring spatial analogs (locations whose current conditions resemble what is expected in the future in a target location) as a way to better communicate climate change risk and create networks of locations that can learn from each other about best management adaptations.
  • Digital Agriculture Focused Hackathons
    • In partnership with Microsoft, Innov8Ag, and the Cascadia Initiative, we are planning hackathon style events to increase awareness of capabilities in the Digital Agriculture space and foster partnerships and innovation.


  • NSF
  • Washington State Department of Agriculture
  • WA Department  of Ecology
  • Microsoft
  • Innov8Ag

Core Faculty:

Claudio Stockle
Biological Systems Engineering

Eric Russell
Civil and Environmental Engineering

Jan Boll
Civil and Environmental Engineering

Jenny Adam
Civil and Environmental Engineering

John Harrison
School of the Environment

Jonathan Yoder
Economic Sciences

Kirti Rajagopalan
Biological Systems Engineering

Michael Brady
Economic Sciences

Sasha Richey
Civil and Environmental Engineering

Von Walden
Civil and Environmental Engineering