Constraining a complex biogeochemical model for CO 2 and N 2 O emission simulations from various land uses by model–data fusion

摘要: Abstract. This study presents the results of a combined measurement and modelling strategy to analyse N2O CO2 emissions from adjacent arable land, forest grassland sites in Hesse, Germany. The measured reveal seasonal patterns management effects, including fertilizer application, tillage, harvest grazing. annual fluxes are 4.5, 0.4 0.1 kg N ha−1 a−1, 20.0, 12.2 3.0 t C ha−1 a−1 for sites, respectively. An innovative model–data fusion concept based on multicriteria evaluation (soil moisture at different depths, yield, emissions) is used rigorously test LandscapeDNDC biogeochemical model. model run Latin-hypercube-based uncertainty analysis framework constrain parameter derive behavioural runs. indicate that generally capable predicting trace gas emissions, as evaluated with RMSE objective function. shows reasonable performance simulating ecosystem C N balances. helps detect remaining errors, such missing (e.g. freeze–thaw cycling) or incomplete processes respiration rates after harvest). further elucidates identification input sources uptake through shallow groundwater during vegetation period) validation data winter months). Guidance provided improve structure field measurements advance landscape-scale predictions.