Estimation of daily CO2 fluxes and of the components of the carbon budget for winter wheat by the assimilation of Sentinel 2-like remote sensing data into a crop model

Croplands contribute to greenhouse gas emissions but also have the potential to mitigate climate change through soil carbon storage. However, there is a lack of tools based on objective observations for assessing cropland C budgets at the plot scale over large areas. Such tools would allow us to more precisely establish the contribution of an agricultural plot to net CO₂ emissions according to the plot management and identify levers for improving the C budget. In this study, we present a diagnostic regional modelling approach, called SAFY-CO₂, that assimilates high spatial and temporal resolution (HSTR) optical remote sensing data in a simple crop model and evaluate the performance of this approach in quantifying crop production and the main components of the annual carbon budget for winter wheat.The SAFY-CO₂ model simulates daily crop development (biomass, partition to leaves, etc.), the components of net ecosystem CO₂ fluxes, and the annual yield and net ecosystem carbon budget (NECB).Multi-temporal green area index (GAI) maps derived from HSTR data from the Formosat-2 and SPOT satellites were used to calibrate the light-use efficiency and phenological parameters of the model. Data from the literature were used to set a priori values for a set of model parameters, and a large dataset of in situ data was used for model validation. This dataset includes 8 years of eddy-covariance net CO₂ flux measurements and GAI, biomass and yield data acquired at 2 instrumented sites in southwest France. Biomass and yield data from 16 fields in the study area between 2005 and 2014 were also used for validation.The SAFY-CO₂ model is able to reproduce both GAI dynamics (RRMSE = 14%, R² = 0.97) and biomass production and yield (RRMSE of 27% and 21%, respectively) with high precisions under contrasting climatic, environmental and management conditions. Additionally, the net CO₂ flux components estimated by the model generally agreed well with in situ data and presented very good and significant correlations (RMSE of 1.74, 1.13 and 1.29 gC.m⁻².d⁻¹ for GPP, Rₑcₒ and NEE, respectively; R² of 0.90, 0.75 and 0.85 for GPP, Rₑcₒ and NEE, respectively) over the 8 studied years. This study also highlights the importance of accounting for post-harvest vegetative events (spontaneous re-growth, weed development and cover crops) for an accurate calculation of the annual net CO₂ flux. This approach requires a limited number of input parameters for estimating yield and net CO₂ flux components, which is promising for regional/global-scale applications based on Sentinel 2-like data; however, the approach requires plot-scale data concerning organic amendments and straw management (exportation) in animal farming systems to calculate field C budgets.