Publication | Open Access
Approaches and concepts of modelling denitrification: increased process understanding using observational data can reduce uncertainties
54
Citations
67
References
2020
Year
EngineeringBiogeochemical ModelEarth ScienceData ScienceUncertainty QuantificationManagementSystems EngineeringN CycleModeling And SimulationProcess MeasurementBiogeochemistryBiogeochemical CycleProcess AnalysisN CyclingIncreased ProcessProcess Systems EngineeringObservational DataSoil Biogeochemical CyclingProcess IntensificationSoil StructureProcess ControlBiogeochemical ProcessProcess ModellingData Modeling
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.
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