Liu et al. (2026) Modeling maize productivity and N2O emissions under surface and subsurface drip fertigation in current and future climates

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Date: 2026-08-22
• Authors: Huan Liu, Guillermo Guardia, Grant Brian, Ward Smith, Budong Qian, Jørgen Eivind Olesen, Diego Ábalos
• DOI: 10.1016/j.agwat.2026.110716

Research Groups

• Department of Agroecology, Aarhus University, Denmark
• Departamento de Química y Tecnología de Alimentos, ETSI Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Spain
• Centro de Estudios e Investigación para la Gestión de Riesgos Agrarios y Medioambientales (CEIGRAM), Ciudad Universitaria, Madrid, Spain
• Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa, ON, Canada

Short Summary

This study evaluates the performance of the DeNitrification-DeComposition model (DNDCv.CAN) in simulating maize yield and N2O emissions under different drip fertigation systems and N sources in Mediterranean conditions. The model is then used to project future climate scenarios and identify potential drivers of yield loss and N2O increase.

Objective

• Evaluate the performance of DNDCv.CAN in simulating crop growth, soil N cycling, and N2O emissions under various management practices.
• Assess the impact of climate change on maize productivity and N2O emissions under different drip fertigation systems and N sources.
• Identify potential drivers of yield loss and N2O increase under future climate scenarios.

Study Configuration

• Spatial Scale: Mediterranean region, Spain
• Temporal Scale: 2020-2100

Methodology and Data

• Models used: DeNitrification-DeComposition model (DNDCv.CAN)
• Data sources: Field experiment data from a two-year study in Spain, climate projections from five global climate models (GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1–2-HR, MRI- ESM2–0 and UKESM1–0-L)

Main Results

• The model adequately simulated crop yield, grain N content, and cumulative N2O emissions under different drip fertigation systems and N sources.
• Climate change projections indicate consistent increases in average growing season temperature (Tave) and heating degree-days (HDD), alongside decreasing rainfall.
• Model simulations projected that pooled mean maize grain yield would decline by 14.6~56.2% under future climate conditions, with the magnitude of yield reduction varying between subsurface and surface drip irrigation systems and across N fertilizer sources.
• The pooled mean N2O emissions increased by 27.2~52.7% under future climate scenarios.

Contributions

• This study provides a comprehensive evaluation of the performance of DNDCv.CAN in simulating crop growth, soil N cycling, and N2O emissions under various management practices.
• The results highlight the importance of considering climate change impacts on maize productivity and N2O emissions when designing and implementing climate-resilient management practices.

Funding

• This research was funded by the Science and Technology Branch, Agriculture and Agri-Food Canada (project code: [insert project code]).
• Additional funding was provided by the Department of Agroecology, Aarhus University, Denmark.

Citation

@article{Liu2026Modeling,
  author = {Liu, Huan and Guardia, Guillermo and Brian, Grant and Smith, Ward and Qian, Budong and Olesen, Jørgen Eivind and Ábalos, Diego},
  title = {Modeling maize productivity and N2O emissions under surface and subsurface drip fertigation in current and future climates},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2026.110716},
  url = {https://doi.org/10.1016/j.agwat.2026.110716}
}