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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Soil Management and Sugarbeet Research » Research » Publications at this Location » Publication #373570
Research Project: Management Practices for Long Term Productivity of Great Plains Agriculture

Location: Soil Management and Sugarbeet Research

Title: Approaches and concepts of modelling denitrification: Increased process understanding using observational data can reduce uncertainties

Author
item Del Grosso, Stephen - Steve
item SMITH, WARD - Agriculture And Agri-Food Canada
item KRAUS, DAVID - Karlsruhe Institute Of Technology
item MASSAD, RAIA - Aarhus University
item VOGELER, IRIS - Inland Northwest Research Alliance, Inra
item FUCHS, KATHRIN - Karlsruhe Institute Of Technology

Submitted to: Current Opinion in Environmental Sustainability
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/16/2020
Publication Date: 8/12/2020
Citation: Del Grosso, S.J., Smith, W., Kraus, D., Massad, R., Vogeler, I., Fuchs, K. 2020. Approaches and concepts of modelling denitrification: Increased process understanding using observational data can reduce uncertainties. Current Opinion in Environmental Sustainability. 47:37-45. https://doi.org/10.1016/j.cosust.2020.07.003.
DOI: https://doi.org/10.1016/j.cosust.2020.07.003

Interpretive Summary: Denitrification is a key but poorly quantified component of the nitrogen cycle. Because it is difficult to measure the gaseous and soluble nitrogen components of denitrification with sufficient intensity, models of varying scope and complexity have been developed and applied to estimate how vegetation cover, land management and environmental factors such as soil type and weather interact to control these variables. In this paper we assess the strengths and limitations of different modeling approaches, highlight major uncertainties, and suggest how different observational methods and process-based understanding can be combined to better quantify nitrogen cycling. Representation of how biogeochemical and physical soil factors influence denitrification rates and products and ensemble approaches can increase accuracy without requiring additional site level model inputs.

Technical Abstract: Denitrification is a key but poorly quantified component of the N cycle. Because it is difficult to measure the gaseous (NOx, N2O, N2) and soluble (NO3) components of denitrification with sufficient intensity, models of varying scope and complexity have been developed and applied to estimate how vegetation cover, land management and environmental factors such as soil type and weather interact to control these variables. In this paper we assess the strengths and limitations of different modeling approaches, highlight major uncertainties, and suggest how different observational methods and process-based understanding can be combined to better quantify N cycling. Representation of how biogeochemical (e.g., org. C., pH) and physical (e.g., soil structure) factors influence denitrification rates and product ratios and ensemble approaches can increase accuracy without requiring additional site level model inputs.