Testing Denitrification Functions of Dynamic Crop Models
1997
Marchetti, R. | Donatelli, M. | Spallacci, P.
Denitrification (DN) has an important role in models simulating soil nitrate leaching, because denitrification losses influence the soil N budget, hence the amount of nitrate available for leaching. In spite of the importance of DN estimate, the behavior of submodels simulating DN losses is not well known. The aim of this study was to improve the knowledge of the behavior of submodels simulating DN losses in selected crop growth/N-leaching models. To remove the interference of the other processes on the results, we isolated the algorithms predicting the denitrification rate (DNR) and applied them to three data sets selected from the available literature. Denitrification subroutines were taken from the models EPIC, CropSyst, CREAMS, GLEAMS, CERES-N, and NLEAP. A preliminary sensitivity analysis emphasized how quite similar algorithms can give rise to considerably different predictions. The measured vs. predicted values comparison confirmed DNR to be remarkably affected by the soil water content (SW) relationship with soil water values at field capacity and/or at saturation. CERES-N, CREAMS, GLEAMS, and EPIC submodels underestimated even up to 100% the number of occasions where DNR > 0, since they simulated the DN process only when SW values were higher than SW at field capacity, whereas in real systems DN occurs even at lower SW values. Results suggest that DN modeling should take into greater account the contribution to DN losses during aerobic conditions. The large natural variation of DNR measurements invalidates the use of statistical criteria for the comparison of measured vs. estimated DN values in deterministic models. Research supported by the MiRAAF, Finalized Project “Produzione Agricola Nella Difesa dell'Ambiente (PANDA)”, Subproject 1, Paper no. 21, Series 1.
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