Sensitivity Analysis of a Source Partitioning Method for H2O and CO2 Fluxes via Large Eddy Simulations

Scanlon and Sahu (2008) and Scanlon and Kustas (2010) proposed a source partitioning method (SK10 in the following) to estimate contributions of transpiration, evaporation, photosynthesis, and respiration to H₂O and CO₂ fluxes obtained by the eddy covariance method. High frequency time series are needed, and the source partitioning is estimated based on the separate application of the flux-variance similarity theory to the stomatal and non-stomatal components of the regarded fluxes, as well as on additional assumptions on water use efficiency (WUE) on the leaf scale. The estimated WUE has been declared to influence the performance of the partitioning method strongly.

Evaluations of SK10 with field observations suffer from the fact that the real source partitioning is usually not known, and that various disturbances may influence the correlation between H₂O and CO₂ fluctuations. Therefore, we conducted Large Eddy Simulations (LES), simulating the turbulent transport of H₂O and CO₂ for contrasting vertical distributions of the canopy sources, as well as varying relative magnitudes of soil sources and canopy sink/source. SK10 was applied to these synthetic high-frequency data and the partitioning performance could be analyzed depending on canopy type, measurement height, and given sink-source-distributions. For a satisfying performance of SK10, a certain degree of decorrelation of the H₂O and CO₂ fluctuations was needed. This decorrelation is enhanced by a clear separation between soil sources and canopy sources, and for observations within the roughness sublayer. The expected dependence of the partitioning results to the WUE input could be observed, where a wrong estimation of WUE affected the flux components of soil sources stronger than components of the canopy sink/source. As a new finding, our LES study indicated that next to a precise WUE estimation, the validity of the key assumptions made by Scanlon and Sahu (2008) in the method’s derivation is a crucial point for a correct application of SK10. Therefore, a thorough assessment of the conditions at study sites affecting the validity of these assumptions would be necessary.

Scanlon, T.M., Sahu, P., 2008. On the correlation structure of water vapor and carbon dioxide in the atmospheric surface layer: A basis for flux partitioning. Water Resources Research 44 (10), W10418, 15 pp, https://doi.org/10.1029/2008WR006932.

Scanlon, T.M., Kustas, W.P., 2010. Partitioning carbon dioxide and water vapor fluxes using correlation analysis. Agricultural and Forest Meteorology 150 (1), 89‑99, https://doi.org/10.1016/j.agrformet.2009.09.005.