Uncertainties in model predictions of nitrogen fluxes from agro-ecosystems in Europe

To assess the responses of nitrogen and greenhouse gas emissions to pan-European changes in land cover, land management and climate, an integrated dynamic model, INTEGRATOR, has been developed. This model includes both simple process-based descriptions and empirical relationships and uses detailed G...

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Bibliographic Details
Main Authors: J. Kros, G. B. M. Heuvelink, G. J. Reinds, J. P. Lesschen, V. Ioannidi, W. De Vries
Format: Article
Language:English
Published: Copernicus Publications 2012-11-01
Series:Biogeosciences
Online Access:http://www.biogeosciences.net/9/4573/2012/bg-9-4573-2012.pdf
Description
Summary:To assess the responses of nitrogen and greenhouse gas emissions to pan-European changes in land cover, land management and climate, an integrated dynamic model, INTEGRATOR, has been developed. This model includes both simple process-based descriptions and empirical relationships and uses detailed GIS-based environmental and farming data in combination with various downscaling methods. This paper analyses the propagation of uncertainties in model inputs and parameters to outputs of INTEGRATOR, using a Monte Carlo analysis. Uncertain model inputs and parameters were represented by probability distributions, while spatial correlation in these uncertainties was taken into account by assigning correlation coefficients at various spatial scales. The uncertainty propagation was analysed for the emissions of NH<sub>3</sub>, N<sub>2</sub>O and NO<sub>x</sub>, N leaching to groundwater and N runoff to surface water for the entire EU27 and for individual countries. Results show large uncertainties for N leaching and runoff (relative errors of ∼ 19% for Europe as a whole), and smaller uncertainties for emission of N<sub>2</sub>O, NH<sub>3</sub> and NO<sub>x</sub> (relative errors of ∼ 12%). Uncertainties for Europe as a whole were much smaller compared to uncertainties at country level, because errors partly cancelled out due to spatial aggregation.
ISSN:1726-4170
1726-4189