« Back to Results
Integrated Assessment Models (IAMs) for Navigating the Intersections of Agriculture, Climate Change, Trade and Water Quality
Saturday, Jan. 6, 2024
10:15 AM - 12:15 PM (CST)
Agricultural and Applied Economics Association
West Virginia University
Nutrient Management in the Mississippi River Basin Under Climate Change
The impact of climate change on nitrogen (N) nutrient management in agriculture is complex and multifaceted, as it affects various stages of the nutrient cycle. Shifts in climate patterns, including temperature and precipitation timing and intensity, are expected to affect crop nutrient uptake efficiency, denitrification, and nutrient concentration in water bodies. Achieving the same nutrient management goal in the Mississippi River Basin may become more costly under climate change. To test this hypothesis, we use an integrated system with agro-ecological Agro-IBIS model and a grid-resolving partial equilibrium economic model SIMPLE-G to link biophysical transfer functions (crop yield and N loss responses to N fertilizer application) and economic decisions (inputs use). We set a common aggregated N loss reduction target and obtain the optimal spatial N application rate reduction under different climate conditions. Because grid-specific production technology and N loss response curves are embedded in the economic model that maximizes farm income subject to N use constraint, the equilibrium balances the trade-off between yield penalty and mitigation outcomes. Preliminary results suggest that climate change could increase N loss and the cost to reach a leaching mitigation target. The results from a model with coupled feedback between human decisions and biophysical systems are significantly different from the decoupled model results. Our raster-based model also identifies the hotspots of N loss under future climate to facilitate the targeting of conservation policies.
A Dynamic Regional Integrated Assessment Model to Assess the Impacts of Deglobalization and Environmental Stewardship on the Regional Economy and Water Quality
The global economy has been in turbulent times, disordered by a sequence of shocks – the pandemic, trade war between the US and China, and the Russian invasion of Ukraine – with no respite in between. Current global uncertainty has a significant impact on the global commodity market and international collaboration toward addressing global challenges, such as climate change. This, in turn, prompts adjustments in regional economic decisions and individual land use and management practices, which ultimately affect regional environmental quality. We develop a dynamic regional integrated assessment model (IAM) of the Great Lakes region, incorporating a detailed representation of agriculture, energy, transportation, and manufacturing sectors, interactions with local- and state-scale land use change that also account for individual heterogeneity in agricultural land management practices, and water quality assessment. By integrating three sub-models of a regional-level forward-looking dynamic model, a state-level static computable general equilibrium model, and a local-level land use change model, this IAM enables a comprehensive and theoretically consistent integration from global conditions through individual-level decision-making. The model simulates five scenarios associated with a distinctive combination of global commodity prices, CO2 prices, climate conditions, productivity, population, and economic growth. The results highlight the impacts of the heterogenous global conditions on regional-, state-, local-, and individual-level decisions, manifested in shifts in land use and land cover, agricultural production, and, as a result, nutrient application, and water quality. The research provides insights into relations between regional economic decisions and environmental quality under changing global conditions.
U.S.-China Agricultural Trade and Environmental Outcomes: The Case of Nutrient Runoff to the Gulf of Mexico
Trade, agricultural production and environmental outcomes are interdependent. The U.S. has is a major agricultural exporter with well-documented and significant nutrient runoff externalities that have dogged academic researchers, practitioners and regulators for decades. Yet, the interdependencies between agricultural trade and water pollution have not been sufficiently studied. This paper quantifies the relationship between nitrogen runoff to the Gulf of Mexico and U.S. agricultural exports to China. First, we provide a theoretical framework, which sets a foundation for the empirical analysis and illustrates theoretical expectations for the effect of trade tariffs on agricultural production externality and the effect of externality regulation on exports. Next, we use an Integrated Assessment Model (IAM) that combines a county scale land use and production in the US with a price endogenous partial equilibrium commodity market representation and process-based Soil and Water Assessment Tool (SWAT) to link trade, production, and nitrogen (N) runoff to the Gulf of Mexico. The model covers county scale production of corn, soybean, wheat and sorghum explicitly and all other crops combined as part of the crop rotation specifications. Trade includes the U.S., China and the rest of the world (ROW). We show that a 25% Chinese tariff on U.S. soybean and corn imports increases annual N runoff to the Gulf by 800 metric tons (0.2%) as soybean production in the Mississippi-Atchafalaya River Basin is displaced with more N-intensive crops, including corn. We also observe that reducing N runoff to the Gulf by 10% decreases U.S. corn export to China by 14.5%, which is similar to the effect of a 25% Chinese tariff on corn and soybean.
Catherine Louise Kling