Skip to Main content Skip to Navigation
Journal articles

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

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 combined with ensemble approaches may increase accuracy without requiring additional site level model inputs.
Document type :
Journal articles
Complete list of metadata

https://hal.inrae.fr/hal-03145708
Contributor : Marina Pavlidès <>
Submitted on : Thursday, February 18, 2021 - 3:32:18 PM
Last modification on : Thursday, June 17, 2021 - 3:11:14 AM

Links full text

Identifiers

Citation

Stephen del Grosso, Ward Smith, David Kraus, Raia Silvia Massad, Iris Vogeler, et al.. Approaches and concepts of modelling denitrification: increased process understanding using observational data can reduce uncertainties. Current Opinion in Environmental Sustainability, Elsevier, 2020, 47, pp.37-45. ⟨10.1016/j.cosust.2020.07.003⟩. ⟨hal-03145708⟩

Share

Metrics

Record views

38