Modeling Linked Behavioral and Natural FEW Systems:
Key Gaps and Challenges
Madhu Khanna
University of Illinois
Research Problem: Meeting the demands for FEW while reducing multiple environmental
externalities - incorporating the potential for emerging productivity enhancing technologies (cellulosic
biofuels, big data enabled precision farming) and designing policy incentives.
• Scale of analysis: Microunit of analysis in behavioral models vs ecosystem models
• Trade-off between heterogeneity and overall geographical scale of analysis
• Technological change: Dynamic and spatially heterogeneous
• Involves lumpy, indivisible investments
• Affected by non-economic behavioral factors;
• Risk, uncertainty, adaptive expectations and absence of perfect foresight
• Modeling multiple externalities requires linking more than one type of
biophysical/hydrological model (SWAT, DayCent, GREET) with economic model
• Consistency across models
• Designing mix of policy instruments that achieve multiple environmental objectives that are
complements/conflicting
• Uncertainty due to natural variability: Implications for policy
Recent publications
• Housh, M., M. Khanna, and X. Cai, “Mix of First and Second
Generation Biofuels to meet Multiple Environmental Objectives:
Implications for Policy at a Watershed Scale,” Water Economics and
Policy (in press 2015).
• Housh, M. et al, “Managing Multiple Mandates: A System of Systems
Model to Analyze Strategies for Producing Cellulosic Ethanol and
Reducing Riverine Nitrate Loads in the Upper Mississippi River Basin,”
Environmental Science and Technology, (in press 2015).
• Hudiburg et al. “Reducing Fossil Energy Use and GHG Emissions with
Biofuels: An Integrated Assessment” Nature Energy, forthcoming
(January 2016).