Sources of uncertainty in simulating crop N2O emissions under contrasting environmental conditions

Abstract

Nitrogen fertilization is a key agronomic lever for high crop productivity, but also an important source of N2O emission, a potent greenhouse gas. Process-based agroecosystem simulation models are popular tools for managing the timing and amount of fertilization, and help reduce N2O emissions. However, accurate simulation of N2O emissions at field scale is still a challenge due to the spatial and temporal variability of the soil conditions. In this study, we investigated the sources of structural uncertainty in predicting N2O emissions under a wide range of pedo-climatic conditions using a representative field data set. We implemented the same nitrification/denitrification/N2O emission formalism in three different agroecosystem models and analyzed how the inter-model variability of variables involved in nitrification and denitrification processes, affected the simulated N2O emissions. We characterized the dispersion of the key variables (water-filled pore space, NO3− and NH4+ concentration, and soil temperature) between models and we evaluated the effect of variable uncertainty on N2O emissions uncertainty using a sensitivity analysis. We also analyzed model errors over a wide range of soil-climate conditions to identify the most challenging conditions for simulation, which require further model improvement. Our results highlighted that the simulation of the timing and amplitude of the NO3− and NH4+ peaks was highly variable between agroecosystem models, with an important impact on N2O emission. These peaks occurred mainly after fertilization or incorporation of crop residues, and the different representations of fertilization and mineralization between the models had a major effect on the simulation of N2O emissions. Our analysis also emphasized that wet acidic soils with high denitrification potential are more challenging for models to simulate.