Evaluating the impact of soil microclimatic conditions on N2O emission peaks under different agricultural management practices using measured and simulated daily time-step data

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N2O accounts for approximately 6% of annual global greenhouse gases emissions in terms of CO2 equivalents, and since anthropogenic N2O emissions are largely associated with agricultural activities, their assessment is increasingly important for evaluating the mitigation potential of alternative soil and crop management practices. Indeed, the interactions between atmospheric and soil microclimates, along with cropping system management, influence the spatial and temporal variability of N2O emissions.Therefore, the objective of this research is to evaluate the effects of microclimatic conditions on N2O emission peaks under different management practices using daily measured data, and to compare the impact of two soil water content simulation approaches on N2O emissions temporal variability simulation at the field level.The field trial, currently ongoing, was established in September 2023 in Landriano (Italy, Cfa climate) to investigate a two-year silage crop rotation with double cropping (barley, soybean, and maize) including slurry application. Three management levels are being studied: conventional – crop residue removal and plowing; semi-conservative – crop residue mulching and minimum tillage; no-tillage – crop residue mulching and sod-seeding. The monitoring station, installed in the experimental field, consists of a weather station, and of a shelter housing gas analysers (LI-COR LI-850 and LI-7820), a multiplexer, and 12 automatic chambers. Each chamber is equipped with sensors to measure the internal air pressure and temperature, and with soil probes to measure soil temperature and water content (Campbell Scientific PT100 and CS616).The measured variables are used to calibrate ARMOSA (Colombi et al., 2024), a process-based cropping system model operating at a daily time step and field scale. Soil water dynamic is simulated using two different approaches implemented in ARMOSA: the cascading travel time method (Savabi and Williams, 1995), and Richard’s equation (Coppola et al., 2024) as integrated in the SWAP model. The calibrated model is then used to evaluate the performance of these soil water balance simulation approaches, both in reproducing soil microclimate conditions and in their influence on the simulation performance of N2O emission peaks. AcknowledgementsThis study was carried out within the Agritech National Research Center and received funding from the European Union Next-Generation EUGeneration EU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR)—MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4—D.D. 1032 17 June 2022, CN00000022).ReferencesColombi, A., et al., 2024. A sound understanding of a cropping system model with the global sensitivity analysis. Environ. Model. & Softw., 173, 105932Savabi, M.R., Williams, J.R., 1995. WATER EROSION PREDICTION PROJECT HILLSLOPE PROFILE AND WATERSHED MODEL DOCUMENTATION: WATER BALANCE AND PERCOLATION. USDA-ARS National Soil Erosion Research Laboratory, West Lafayette, IndianaCoppola A., et al., 2024. Monitoring and modelling fluxes of water and nutrients to surface drainage network from irrigated agricultural fields in a hydraulically reclaimed coastal area. Ecohydrology, 17, 8

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