Simulating site-specific nitrogen mineralization dynamics in a Swedish arable field

Author： Karlsson Thord Delin Sofia Kätterer Thomas Berglund Kerstin Andrén Olof

ISSN： 0906-4710

Source： Acta Agriculturae Scandinavica, B, Vol.61, Iss.4, 2011-05, pp. : 333-344

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Abstract

The objective of this work was to test whether a dynamic soil C and N model using site-specific information improved estimates of apparent net N mineralization compared with regressions only based on static soil properties. This comparison was made using data from a 34-point sampling grid within a Swedish arable field during two growing seasons, using a simple carbon balance and nitrogen mineralization model (ICBM/N) for the dynamic approach. Three free model parameters were simultaneously optimized using non-linear regression to obtain the best model fit to the data from all grid points and both years. Calculated annual mean net mineralization (Nm_sim) matched the measured Nm mean exactly, and was 44 and 71 kg N ha⁻¹ for the two growing seasons 1999 and 2000, respectively. However, the variability in calculated Nm_sim values among the 34 grid points was smaller than that measured, and only a small proportion of the variation within a single year was explained by the model. Despite this, the model explained 56% of the total variation in Nm during the two growing seasons, mainly due to the good fit to the seasonal overall difference. Significant factors influencing net mineralization included the soil environment controlling mineralization, total N in soil organic matter and N in crop residues. Uncertainties in estimation of θ _fc and θ _wp (soil water content at saturation and wilting point) and the possible influence of unknown horizontal and vertical water flows made high-precision calculations of soil water content difficult. The precision and general applicability of the actual measurements thus set limits for estimating critical parameters, and the limitations of both the experimental design and the model are discussed. It is concluded that improvements in precision in sampling and analysis of data from the grid points are needed for more critical hypothesis testing.