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  5. Integrated Assessment Models (IAMs) for Navigating the Intersections of Agriculture, Climate Change, Trade and Water Quality
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Integrated Assessment Models (IAMs) for Navigating the Intersections of Agriculture, Climate Change, Trade and Water Quality

Paper Session

Saturday, Jan. 6, 2024 10:15 AM - 12:15 PM (CST)

Grand Hyatt, Seguin B
Hosted By: Agricultural and Applied Economics Association
  • Chair: Levan Elbakidze, West Virginia University

Nutrient Management in the Mississippi River Basin Under Climate Change

Jing Liu
,
Purdue University
Kelsie Ferin
,
University of Wisconsin-Madison

Abstract

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 Changing Globalization and Environmental Stewardship on the Regional Economy and Water Quality

Junyoung Jeong
,
Ohio State University
Yongyang Cai
,
Ohio State University
Brian Cultice
,
Ohio State University
Elena Irwin
,
Ohio State University
Jeff Bielicki
,
Ohio State University

Abstract

Changes in the global economy and climate system have large and wide-ranging repercussions for local and regional economies and ecosystems. Here we focus on global-to-local linkages that are hypothesized to impact water quality outcomes within a five-state Great Lakes-Corn Belt region, which includes some of the most intensive agricultural region of the Midwest. We develop a dynamic integrated assessment model (IAM) that links the regional economy to global conditions, local land use change, and water quality outcomes and use a scenarios framework to assess the likelihood that phosphorus reduction targets for Lake Erie are met by 2050 under a range of plausible global and regional conditions. We examine the relative role that global economic and climate conditions play in regional land use and water quality outcomes and the extent to which local land stewardship incentives and best management practices (BMPs) can offset the potential negative effects of global economic and environmental changes. By integrating 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 regional and local decision-making. The model simulates five scenarios defined by distinctly different combinations of global commodity prices, CO2 prices, climate conditions, productivity, population, and economic growth. Our results reveal that success in attaining the policy target is relatively uncertain and highly dependent on future economic, environmental, and policy conditions. We find that only two of the scenarios are projected to attain the 40 percent spring DRP and TP reduction targets nine out of ten years by the 2030’s. Other results confirm that lower commodity prices generally lead to reduced cropland acres and are mostly associated with better water quality outcomes. However, greater intensification of cropland use is not associated with greater water pollution, a result that may be driven by the relatively high adoption rates for subsurface placement that are reached in later years across scenarios. Taken together, these results demonstrate the potential for local policies to incentivize BMP adoption at levels that can act as a buffer to uncertain, changing global conditions.

U.S.-China Agricultural Trade and Environmental Outcomes: The Case of Nutrient Runoff to the Gulf of Mexico

Levan Elbakidze
,
West Virginia University
Yuelu Xu
,
Manaaki Whenua-Landcare Research
Philip W. Gassman
,
Iowa State University
Haw Yen
,
Bayer Crop Science
Jeffrey G. Arnold
,
USDA

Abstract

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.

Discussant(s)
Catherine Louise Kling
,
Cornell University
JEL Classifications
  • A1 - General Economics