Soil quality analysis: innovative validation and modeling of carbon and nitrogen transformation dynamics in middle Volga's forest-steppe soils

Soil quality analysis: innovative validation and modeling of carbon and nitrogen transformation dynamics in middle Volga's forest-steppe soils

This study evaluates the Denitrification-Decomposition (DNDC) and Rothamsted Carbon (RothC) models for simulating carbon and nitrogen compound transformations in the forest-steppe soils of the Middle Volga region. The research holds significance for agriculture, particularly with the growing focus on carbon farming and the requirement to model the climate effect over years depending on the selected practice. Three scenarios were chosen to compare the models: no-till since 2014, no-till since 2017, and conventional tillage. The DNDC model revealed a strong correlation between modeled and measured Soil Organic Carbon (SOC) in the 0-10 cm soil layer. The highest SOC levels were found in the soils under no-till since 2017. In 2021, CO₂ emissions were highest under conventional tillage (1119.2 kg C ha^-1) and significantly lower in no-till systems: 544.9 kg C ha^-1 (since 2017) and 473.1 kg C ha^-1 (since 2014). The DNDC model showed the highest annual microbial biomass carbon (MBC) in forest soils (129.4 kg C ha^-1). In croplands, no-till sunflower fields had higher MBC (73.3 vs. 53.0 kg C ha^-1). N₂O emissions were lowest in no-till fields since 2017 (0.516 kg N ha^-1), while conventional tillage and no-till since 2014 showed similar emissions (1.366 and 1.340 kg N ha^-1). The DNDC model outperformed RothC in modeling plant growth, SOC, MBC, and emission dynamics for NH₄⁺, NO₃^-, CO₂, N₂O, NH₃, and CH₄. These differences in the modeled results can cause ambiguity in terms of forecasting climatic effect. That is why it is necessary either to choose a generally accepted model whose results will be acceptable in international projects or organise specific research to see which model provides for better results.