| Title | Carbon Farming practices assessment: Modelling spatial changes of Soil Organic Carbon in Flanders, Belgium |
|---|---|
| ID_Doc | 66888 |
| Authors | Spotorno, S; Gobin, A; Vanongeval, F; Del Borghi, A; Gallo, M |
| Title | Carbon Farming practices assessment: Modelling spatial changes of Soil Organic Carbon in Flanders, Belgium |
| Year | 2024 |
| Published | |
| Abstract | Carbon sequestration in soils is a strategy to mitigate climate change and promote sustainable soil management. Since the European Union (EU) stimulates the reduction of greenhouse gases (GHG) from the atmosphere, the necessity to explore innovative approaches to sequester carbon in agricultural landscapes is becoming urgent. Carbon Farming (CF) has emerged as a promising program to mitigate climate change in agriculture but there is still a lack of agreement on which tools can be used to calculate Soil Organic Carbon (SOC) dynamics in this context. Using the RothC model a spatial analysis of SOC in the agricultural parcels of Flanders, Belgium was performed. Two among the various CF practices were simulated: a use of cover crops (CC) and the most common crop rotations adopted in the area, enriched with the use of cover crops. The performances of the model were evaluated and compared to other studies in areas with similar climate and environments. The selected CF practices can mitigate the carbon emissions from agricultural soils up to 60 % of the current projections. The most sensitive variables in the RothC model that affect the final total SOC, and thus determining the model outcome, are the Business As Usual (BAU) carbon inputs and the initial carbon content. For these variables the Pearson Correlation Coefficient with the change in SOC reached values of -0.78 and -0.50 respectively. To achieve net carbon sequestration in the agricultural soils of Flanders, Belgium, more effective solutions need to be evaluated. Furthermore, a larger amount and accessibility of data are required to reach better modelling performances. |
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