Optimizing land management for nitrogen reduction: a bio-economic spatial model

Authors: Levers, Lucia; Dalzell, Brent; PETERSON, JEFFERY - University Of Minnesota

Submitted to: Environmental Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/21/2025
Publication Date: 3/1/2025
Citation: Levers, L.R., Dalzell, B.J., Peterson, J.M. 2025. Optimizing land management for nitrogen reduction: a bio-economic spatial model. Environmental Management. 377. https://doi.org/10.1016/j.jenvman.2025.124702.
DOI: https://doi.org/10.1016/j.jenvman.2025.124702

Interpretive Summary: Combining bio-physical and economic modeling methods, we estimate that substantial nitrogen reductions can occur by strategically located cover crops. The framework developed here can help target locations within a landscape, minimizing profit loss per kg of nitrogen removed from the landscape. We model farm and farm field based management units, in addition to hydrologic response units, to provide more realistic results. We find that precipitation and yearly differences are a large predictor of land cover effectiveness, which has policy implications for a climate change affected future.

Technical Abstract: We develop a flexible geo-spatial economic framework to optimize land use changes, and estimate profit reductions, under nitrogen effluent benchmarks. We simulate alternative cropping patterns at the hydrologic response unit (HRU) level and with a novel and more realistic management unit approach by combining Soil and Water Assessment Tool model outputs and an economic programming model. We apply our framework to a major Minnesota River Basin watershed, the Cottonwood River watershed, in the state of Minnesota. While perennial crops are more environmentally beneficial, we find that strategically located cover crops can be used as the sole practice to achieve significant nitrogen effluent reduction. A large driver of nitrogen pollution and reduction in profit is yearly variation, a proxy for precipitation volume—indicating that climate change may be particularly impactful in areas like Minnesota, where climate change models predict increasingly rainy springs.