Practical Implications for Watershed Management: Focus on supply chain modeling and future scenario planning
Farm field with cattle grazing and farm buildings in the background. Credit: Nicholas A. Tonelli, CC BY 2.0
Team lead: Caitlin Grady
Students: Paniz Mohammadpour (Penn State), Ji Qi (George Washington University), Tarun Kaminari (George Washington University).
Collaborators: Scenario team, including Michael Gomez, Jason Kaye, Lisa Wagner, Cibin Raj, and David Abler
What Is the Issue?
Despite decades of nutrient management efforts in the Chesapeake Bay Watershed, nitrogen pollution from agriculture remains a persistent challenge, contributing over 40% of the Bay's total nitrogen load. While existing models help simulate nitrogen loads, they have limited insight into how trade and supply chain interactions impact environmental outcomes. When food moves between regions through trade networks, it can hide environmental impacts from consumers and decision-makers. Additionally, as agricultural production is expected to increase to meet growing food demand, understanding how future scenarios might affect nitrogen pollution becomes critical for meeting environmental targets like the Total Maximum Daily Load (TMDL) reduction goals.
Current nitrogen management approaches focus primarily on field-scale practices, but lack comprehensive tools to track nitrogen as it flows through the entire food production chain, from crop production through processing, trade, and consumption. This gap makes it difficult to identify where the biggest opportunities exist for reducing nitrogen losses and how trade patterns might be leveraged to improve overall watershed outcomes.
What Did We Find and Why Does It Matter?
Our research developed two complementary approaches that provide new insights into nitrogen management opportunities in the Chesapeake Bay Watershed.
We created a detailed model that tracks nitrogen flows through the entire food production chain, from fertilizer application to final consumption, including the often-overlooked role of trade. Our analysis revealed that trade actually reduces nitrogen losses in the watershed by approximately 40 million metric tons annually. This happens because the watershed exports more nitrogen-intensive products than it imports, effectively shifting some environmental impacts to other regions. The model showed that corn grain and soybean contribute most to both domestic production and trade flows, while poultry operations create significant regional hotspots of nitrogen loss.
Our forward-looking analysis examined how nitrogen losses might change under different agricultural production and management scenarios through 2050. We found that under business-as-usual conditions, nitrogen losses would increase by 11% by 2030 and 23% by 2050, primarily driven by increased corn and wheat production and steady growth in livestock operations. We also discovered that modest improvements in management practices, such as 10% reductions in fertilizer application rates and feed conversion ratios, fall short of the 25% TMDL reduction targets. Meeting these goals would require 25 –30% reductions in both fertilizer application rates and feed conversion ratios.
What Did We Do?
We developed the Nitrogen Flow model of the Chesapeake Bay Watershed Food production chain that tracks nitrogen through seven distinct stages: crop production, crop processing, live animal production, animal slaughtering/processing, animal product processing, animal product preparation, and consumption. Unlike previous models, ours explicitly accounts for county-level trade flows both within the watershed and with external regions. We used data from the USDA Agricultural Census, Freight Analysis Framework, and an extensive literature review to quantify nitrogen content and conversion factors for major agricultural commodities.
The model operates at the county level across all 195 jurisdictions in the watershed, covering six major crop categories (corn, wheat, soybean, corn silage, alfalfa hay, and other hay) and five animal categories (beef cows, dairy cows, broiler chickens, laying hens, and hogs).
For our forward-looking analysis, we created multiple scenarios combining different levels of agricultural production changes, land use modifications, and nitrogen management strategies.
Figure 1: Below is a conceptual diagram of our system boundary model. We calculated embedded nitrogen in the primary crop and animal supply chains into and outside of the Chesapeake Bay and linked the two boundaries through import and export across the boundary.
Figure 2: The flow chart below outlines how this supply chain model works. The far-left side shows new fertilizer input (inorganic) and recycled fertilizer input (organic manure) beginning the model and moving through each stage of the supply chain from planting corn, soy, and other crops through crop processing, animal feed, animal processing, all the way through end use at the far right of the diagram.
Publications completed for this work
Gomez, M., Grady, C., Wainger, L., Cibin, R., Abler, D., Bosch, D., & Kaye, J. (2024). Impacts of future scenarios on the nitrogen loss from agricultural supply chains in the Chesapeake Bay. Environmental Research Letters, 19(8), 084039. https://doi.org/10.1088/1748-9326/ad5d0b
Mohammadpour, P., & Grady, C. (2023). Regional analysis of nitrogen flow within the Chesapeake Bay watershed food production chain inclusive of trade. Environmental Science & Technology, 57(11), 4619–4631. https://doi.org/10.1021/acs.est.2c07391
Mohammadpour, P., Grady, C., Wainger, L., Kaye, J., Abler, D., & Cibin, R. (2025). Systems approach to nitrogen modeling in the Chesapeake Bay: Advancing production chain analysis under future changes. Journal of Environmental Quality. https://doi.org/10.1002/jeq2.70142
