Modeling approaches have emerged to address uncertainties arising from N2O emissions variability, representing a powerful methodology to investigate the two emitting processes (i.e., nitri- fication and denitrification) and to represent the interconnected dynamics among soil, atmosphere, and crops. This work offers an extensive overview of the widely used models simulating N2O under different cropping systems and management practices. We selected process-based models, prioritiz- ing those with well-documented algorithms found in recently published scientific articles or having published source codes. We reviewed and compared the algorithms employed to simulate N2O emissions, adopting a unified symbol system. The selected models (APSIM, ARMOSA, CERES-EGC, CROPSYST, CoupModel, DAYCENT, DNDC, DSSAT, EPIC, SPACSYS, and STICS) were categorized by the approaches used to model nitrification and denitrification processes, discriminating between implicit or explicit consideration of the microbial pool and according to the formalization of the main environmental drivers of these processes (soil nitrogen concentration, temperature, moisture, and acidity). Models’ setting and performance assessments were also discussed. From the appraisal of these approaches, it emerged that soil chemical–physical properties and weather conditions are the main drivers of N cycling and the consequent gaseous emissions.

A Review of the Main Process-Based Approaches for Modeling N2O Emissions from Agricultural Soils / M. Gabbrielli, M. Allegrezza, G. Ragaglini, A. Manco, L. Vitale, A. Perego. - In: HORTICULTURAE. - ISSN 2311-7524. - 10:1(2024 Jan 19), pp. 98.1-98.47. [10.3390/horticulturae10010098]

A Review of the Main Process-Based Approaches for Modeling N2O Emissions from Agricultural Soils

M. Gabbrielli
Primo
;
M. Allegrezza
Secondo
;
G. Ragaglini;A. Perego
Ultimo
2024

Abstract

Modeling approaches have emerged to address uncertainties arising from N2O emissions variability, representing a powerful methodology to investigate the two emitting processes (i.e., nitri- fication and denitrification) and to represent the interconnected dynamics among soil, atmosphere, and crops. This work offers an extensive overview of the widely used models simulating N2O under different cropping systems and management practices. We selected process-based models, prioritiz- ing those with well-documented algorithms found in recently published scientific articles or having published source codes. We reviewed and compared the algorithms employed to simulate N2O emissions, adopting a unified symbol system. The selected models (APSIM, ARMOSA, CERES-EGC, CROPSYST, CoupModel, DAYCENT, DNDC, DSSAT, EPIC, SPACSYS, and STICS) were categorized by the approaches used to model nitrification and denitrification processes, discriminating between implicit or explicit consideration of the microbial pool and according to the formalization of the main environmental drivers of these processes (soil nitrogen concentration, temperature, moisture, and acidity). Models’ setting and performance assessments were also discussed. From the appraisal of these approaches, it emerged that soil chemical–physical properties and weather conditions are the main drivers of N cycling and the consequent gaseous emissions.
nitrogen cycle; nitrification; denitrification; nitrous oxide emissions; greenhouse gas emissions; cropping system simulation model
Settore AGR/02 - Agronomia e Coltivazioni Erbacee
19-gen-2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1030155
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