OPTIMIZING N₂O EMISSION PREDICTIONS: A META-ANALYSIS COMPARING PROCESS-BASED MODELS ACROSS SUB-SAHARAN AFRICAN SOILS

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Abstract
Nitrous oxide (N₂O), a potent greenhouse gas, contributes significantly to climate change, with
agricultural soils being a major source. In sub-Saharan Africa (SSA), increasing fertilization to boost
productivity is expected to elevate N₂O emissions, however data scarcity and regional variability
challenge accurate predictions. This study compares results from literature on three process-based
models (DNDC, DayCent, and APSIM) for simulating soil N₂O emissions, focusing on their input data
requirements and predictive accuracy under SSA conditions. Using literature-derived datasets and
model documentation, we evaluated each model’s ability to simulate key nitrogen fluxes (e.g.,
nitrification, denitrification) and assessed their data needs (e.g., soil properties, climate, management
practices). Results indicated that models like DNDC and APSIM, with moderate data requirements, can
offer robust predictions for data-scarce regions. DayCent and APSIM provide comprehensive flux
simulations but require extensive calibration. These findings highlight trade-offs between model
complexity and applicability in SSA, where data availability often limits detailed simulations. Our
comparison provides a framework for selecting appropriate models based on regional data constraints
and research goals, supporting climate-smart agricultural policies. Future efforts should focus on
integrating remote sensing data and standardizing datasets to enhance model performance in
understudied regions like SSA. Therefore, we are currently in the process of calibrating the CN-model
[1] with data sourced from an arable site (Oensingen) in Switzerland, to ensure precise simulation of
nitrogen fluxes at the Oensingen site. Moreover, we are using QUINCY [2] and the CN-model for SSA
datasets, which were compiled in a meta-analysis by Agredazywczuk et al., 2025 (in preparation).


REFERENCES
1 Stocker, B. D. & Prentice, I. C. CN-model: A dynamic model for the coupled carbon and nitrogen
cycles in terrestrial ecosystems. bioRxiv, 2024.2004.2025.591063 (2024).
https://doi.org/10.1101/2024.04.25.591063
2 Thum, T. et al. A new model of the coupled carbon, nitrogen, and phosphorus cycles in the terrestrial
biosphere (QUINCY v1.0; revision 1996). Geosci. Model Dev. 12, 4781-4802 (2019).
https://doi.org/10.5194/gmd-12-4781-2019
Date Issued
2025-09-12
Publication Type
Conference Item
Subject(s)
Subjects
n2o
•
sub-Saharan Africa
•
cropland
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agriculture
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modeling
•
systematic review
Language(s)
en
Author(s)
Otinga, Abigael
Chepkoilel University College
Barthel, Matti
Njoroge, Ruth
Leitner, Sonja
Zhu, Yuhao
ILRI
Oduor, Collin O
ILRI
Oluoch, Kevin Churchil
Chepkoilel University College
Turco, Fabio
Buchmann, Nina
Six, Johan
Additional Credits
Chepkoilel University College
ILRI
Title of Event
Project(s)
Funding(s)
Access(Rights)
metadata.only
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