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Updated: Jan 13, 2026
08:44
Microplot Design and Plant and Soil Sample Preparation for 15Nitrogen Analysis
Published on: May 10, 2020
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Linking remote sensing with crop modeling for yield and nitrate leaching predictions in Minnesota
Muhammad Tahir1, David J Mulla1
1Department of Soil, Water, and Climate, University of Minnesota, St. Paul, Minnesota, USA.
Journal of Environmental Quality
|January 10, 2026
Summary
Implementing alternative crop rotations and optimizing nitrogen fertilizer rates can significantly reduce nitrate-N leaching losses, protecting groundwater quality. Combining practices like cover cropping and improved irrigation further enhances these environmental benefits.
Area of Science:
- Agricultural Science
- Environmental Science
- Agronomy
Background:
- Protecting regional groundwater quality necessitates upscaling crop yield and nitrate-N leaching assessments under various crop rotations.
- The Environmental Policy Integrated Climate (EPIC) model is a key tool for simulating agroecosystem processes at regional scales.
Purpose of the Study:
- To calibrate and upscale the EPIC model for predicting crop yield and nitrate-N leaching across different crop rotations and management scenarios.
- To evaluate the effectiveness of alternative agricultural practices in reducing nitrate-N leaching on sandy soils.
Main Methods:
- Calibrated the EPIC model using nitrogen rate field trials and satellite-derived crop evapotranspiration (ETc).
- Upscaled model predictions to regional scales using irrigation-water permitting data for 13,375 ha of sandy soils.
- Evaluated four management scenarios: reduced N fertilizer, addition of rye cover crop, auto-irrigation, and conversion to alfalfa-corn rotation.
Main Results:
- Reducing nitrogen fertilizer rates and incorporating rye cover crops decreased nitrate-N leaching losses across tested crop rotations.
- Auto-irrigation strategies and converting continuous corn acreage to alfalfa-corn rotations further reduced nitrate-N leaching.
- Combining all evaluated practices resulted in a significant 27.4% reduction in potential nitrate-N leaching to groundwater.
Conclusions:
- Augmenting the EPIC model with field data and remote sensing provides a robust method for upscaling agroecosystem simulations.
- Alternative crop rotations, optimized nitrogen management, cover cropping, and smart irrigation are effective strategies for mitigating nitrate-N leaching.
- The study demonstrates the potential for regional-scale assessment and management of groundwater quality through integrated agricultural practices.
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