Abstract:
Global forces are intensifying local water quality stresses, yet their character and solutions vary by place, and local responses can, in turn, generate global consequences. This talk introduces a flexible, generalizable Global–to–Local–to–Global modeling framework for sustainability analysis, applied to agricultural water quality management. Built on a transfer function approach, the framework advances integrated biophysical-economic modeling beyond traditional soft coupling methods, where models exchange results sequentially, toward a hard-coupled system that embeds biophysical constraints directly within the economic model architecture. The approach is illustrated through three interconnected studies in the U.S. Corn Belt that evaluate the cost-effectiveness of conservation practices, assess how carbon pricing can jointly curb emissions and nitrogen losses, and trace the nitrogen cascade to compare water quality outcomes from wetland restoration and policy-driven shifts such as declining corn ethanol demand amid the electrical vehicle transition.
Bio:
Dr. Jing Liu is a Senior Research Economist in the Department of Agricultural Economics and the Center for Global Trade Analysis (GTAP) at Purdue University. She also serves as the Science Director of GLASSNET, an international research network advancing data and model integration for global sustainability science. Her research lies at the intersection of natural resources, environmental economics, and policy analysis, with a focus on agricultural sustainability and economic resilience. She employs quantitative economic modeling and spatial analysis to understand how farmers and agricultural markets respond to environmental and policy changes. Her work provides data-driven insights to inform strategies for long-term sustainability in agriculture.