Combining remote sensing products with crop and soil models to estimate changes in soil organic carbon on cropland

Agricultural land is a major contributor to human greenhouse gas emissions, but it is also affected by climate change. At the same time, the recent 4p1000 initiative has identified cropland as having important the potential to sequester atmospheric carbon in the soil.
However, there is currently a lack of robust and accurate tools to assess the carbon budget of cropland at plot level and over large areas. This lack is due to the heterogeneity of the landscape, characterised by a wide range of soil and climatic conditions and many agricultural practices. However, these tools are needed to better understand the contribution of cropland to greenhouse gas emissions and to properly identify the most efficient levers for sequestrating carbon in the soil.
In this study we propose a modelling framework to estimate carbon budgets at plot scale and over large areas. This approach assimilates optical remote sensing products with high spatial and temporal resolution into a crop model (SAFYE-CO2). This model allows the estimation of CO2 fluxes as well as crop productions (biomass and yield) of the main crops and the cover crops. This information is then used as input to a soil model (RothC) to estimate the carbon storage following the introduction of the cover crops into the soil.
This framework is validated using CO2 flux measurements from the ICOS network and cover crop in situ biomass data.
This approach is in line with the search for the 'monitoring, reporting and verification' tools that is needed today to drive the agricultural transition, to enable sustainable agriculture that provides sufficient production in a changing climate, while identifying the best practices to use agricultural land as a way of achieving net zero carbon targets.