Modeling

Background

In the creation of a scientific model to explore greenhouses gases in dairy production systems of the Great Lakes region, researchers are developing a description of a physical system that can predict things about many similar situations. Models are developed using data and observations about the production systems with the application of a mathematical language to predict the impact of similar systems. The value of a model is that we can trust its predictions about similar systems even if we don’t study or gather data from each.

Many well regarded scientific models exist for parts of the dairy production system but not for the system as a whole. The modeling team members of the Sustainable Dairy project are analyzing and integrating several process models across scales by using selected models to assess project monitoring data and investigate common scenarios at the animal, field, and farm levels that represent practices to reduce greenhouse gas emissions and adapt to climate change.
Specific field to watershed-scale models include an Animal Scale Model: Cornell Net Carbohydrate and Protein System (CNCPS); several Field to Watershed Scale Models: DNDC-field, APEX,APEX-EPIC and DAYCENT; a Manure Management Model: DNDC and Manure-DNDC; and a Farm-Scale Model, Integrated Farm System Model (IFSM).

By building upon project modeling work, researchers are able to identify climate change scenarios and impacts for analysis. Modeling team members are also evaluating and improving regional benchmarks that will be integrated into life cycle impact assessment. Process models will be further evaluated against monitored results in Year 3 of the project.

For more information, please contact the Modeling Team Lead: Dr. Olivier Joliet, University of Michigan at ojolliet@umich.edu

Notes from Modelers' Meetings:

2016