Abstract

Highlights This study addressed the inclusion of field-scale soil variability in nitrogen (N) management for corn production. RZWQM2 was calibrated for corn yield and N dynamics on four sandy soil series under supplemental irrigation. Multi-year simulations of corn production under high and low N application rates were analyzed. Results showed room to reduce N use and N leaching without affecting corn production on Coastal Plain sandy soils. Abstract. Nitrogen (N) fertilization contributes significantly to maintain high yields in corn (Zea mays L.) production. In the Southeastern Coastal Plain of the U.S. where soils are sandy with poor water and nutrient holding capacity, a fraction of the N applied to corn fields is often leached from the root zone and becomes unavailable to plants. As these soils belong to various taxonomic classes, research has shown significant corn yield differences among soil series. However, few studies have focused on integrating field-scale soil variability, N leaching, and corn production. To address this knowledge gap, this study used the Root Zone Water Quality Model (RZWQM2) to simulate different N management scenarios in corn production for four sandy soil series under supplemental irrigation. The calibrated model was used to simulate nine consecutive years of corn production under four N management scenarios, including two high rates of N application (rate A = 224 kg N ha-1 with 25 kg N ha-1 at preplant; rate A' = 224 kg N ha-1 without preplant N), and two low rates of N application (rate B = 157 kg N ha-1 with 25 kg N ha-1 at preplant; rate B' = 157 kg N ha-1 without preplant N). Simulation results showed that without preplant N application, N leaching was reduced by up to 17% with no significant impact on corn yield, depending on the soil series. Hence, consideration of field-scale soil variability could help improve N management by reducing N use and N leaching without impacting corn production. Keywords: Corn yield components, Growing season, Modeling, Nitrogen dynamics, RZWQM2, Soil variability.

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