Mechanistic modelling of gross primary production and latent heat flux using SIF observations in different water and light limitation conditions

One of the most efficient ways to estimate carbon assimilation at the ecosystem scale is based on the observations of sun-induced chlorophyll fluorescence (SIF) from satellites coupled with empirical relationships between SIF and gross primary production (GPP). However, there is still a lack of knowledge about the influence of physiological and environmental factors on these relationships. Recently, a process-based light response (MLR) model was developed from the perspective of the light reactions of photosynthesis to mechanistically determine the ecosystem photosynthetic activity from SIF measurements above the canopy. In addition to GPP, the MLR model can also be used to predict the latent heat (LE) flux when coupled with a stomatal conductance model like the unified stomatal optimality (USO) model. The goal of this research is to calibrate and test the MLR-USO model, as well as evaluate its performance at the field scale.

The MLR-USO model was used to estimate GPP and LE at the ICOS station in Lonzée, Belgium (BE-Lon), which was equipped with a field spectrometer (Fluorescence box –FLOX) installed above a winter wheat crop to measure SIF between February and July 2022. The application and evaluation of the coupled MLR-USO model at the canopy scale requires (i) to determine the value of the MLR model parameters, (ii) to calibrate the USO model on previous cropping seasons of winter wheat at BE-Lon, (iii) to calculate the broadband (640-850 nm) SIF emitted by all photosystems II (PSII) from in-situ measurements of directional observed SIF at 760 nm, and (iv) to compare GPP and LE estimates from the MLR-USO model with eddy covariance (EC) flux tower GPP and LE.

The results of this study demonstrate that SIF at the canopy scale captured the dynamics of both water and carbon exchanges over a wide range of environmental conditions, including light and water limiting conditions. Consequently, the MLR-USO model performed well when compared to EC data (RMSE_GPP=6.56 μmolm^-2s^-1 / RMSE_LE=22.79 Wm^-1 at half hourly timescales and RMSE_GPP=4.61 μmolm^-2s^-1 / RMSE_LE=26.75 Wm^-1 at daily timescales). These results support the use of this integrated model containing both a stomatal conductance and a photosynthesis module as an important step towards a better understanding and quantification of carbon and water fluxes at the ecosystem scale, providing also key information for the interpretation of satellite-based SIF.