Replicating measured site-scale soil organic carbon dynamics in the US Corn Belt using the SWAT-C model

Accurate quantification of soil organic carbon (SOC) change is essential for designing effective agricultural practices to maximize agronomic, climatic, and environmental benefits. Here, we modified the SOC algorithms within the Soil and Water Assessment Tool - Carbon (SWAT-C) model and applied it to simulate SOC dynamics across seven sites in the U.S. Corn Belt. We examined multiple methods for estimating the effects of soil tem-perature (3 options), soil water (2 options), and tillage (4 options) on SOC decomposition. We found that model simulation results are sensitive to the choice of methods and identified the best performing combination of methods. Further analyses show that the model captured well SOC dynamics at different sites and soil depths and under different tillage intensities. SWAT-C, as an open-source model, is shared to contribute to future carbon assessment and management in agroecosystems and support robust decision making to promote climate smart agriculture.

Automated summary

Accurate quantification of soil organic carbon (SOC) change is crucial for effective agricultural practices. This study modified the SOC algorithms in the SWAT-C model and applied it to simulate SOC dynamics in the U.S. Corn Belt. The results showed that model simulation results are sensitive to the choice of methods and identified the best combination of methods. Further analysis demonstrated that the model captured SOC dynamics well under different conditions. As an open-source model, SWAT-C contributes to carbon assessment and management in agroecosystems and supports decision making for climate smart agriculture.