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Sensitivity analysis of a source partitioning method for H2O and CO2 fluxes based on high frequency eddy covariance data: Findings from field data and large eddy simulations
- Klosterhalfen, A., Moene, A.F., Schmidt, M., Scanlon, T.M., Vereecken, H., Graf, A.
- Agricultural and forest meteorology 2019 v.265 pp. 152-170
- canopy, carbon dioxide, carbon dioxide production, cropland, eddy covariance, evaporation, forests, leaves, photosynthesis, roughness, simulation models, soil, soil respiration, temperature, terrestrial radiation, time series analysis, transpiration, turbulent flow, water use efficiency
- 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 eddy covariance raw data time series are needed, and the source partitioning is estimated based on separate application of the flux-variance similarity theory to stomatal and non-stomatal components of the regarded fluxes, as well as on additional assumptions on leaf-level water use efficiency (WUE).We applied SK10 to data from two test sites (forest and cropland) and analyzed partitioning results depending on various ways to estimate WUE from available data. Also, we conducted large eddy simulations (LES), simulating the turbulent transport of H2O and CO2 for contrasting vertical distributions of the canopy sinks/sources, as well as for varying relative magnitudes of soil sources and canopy sinks/sources. SK10 was applied to the synthetic high frequency data generated by LES and the effects of canopy type, measurement height, given sink-source-distributions, and input of varying WUEs were tested regarding the partitioning performance. SK10 requires that the correlation coefficient between stomatal and non-stomatal scalar fluctuations is determined by the ratio of the transfer efficiencies of these scalar components, an assumption (transfer assumption in the following) that could be tested with the generated LES data.The partitioning results of the field sites yielded satisfactory flux fractions, when fair-weather conditions (no precipitation) and a high productive state of the vegetation were present. Further, partitioning performance with regard to soil fluxes increased with crop maturity. Results also showed relatively large dependencies on WUE, where the partitioning factors (median) changed by around -57% and +36%. Measurements of outgoing longwave radiation used for the estimation of foliage temperature and WUE could slightly increase the plausibility of the partitioning results in comparison to soil respiration measurements by decreasing the partitioning factor by up to 42%. The LES-based analysis revealed that for a satisfying performance of SK10, a certain degree of decorrelation of the H2O and CO2 fluctuations (here, |ρq’c’| < 0.975) was needed. This decorrelation is enhanced by a clear separation between soil sources and canopy sinks/sources, and for observations within the roughness sublayer. The expected dependence of the partitioning results on the WUE input could be observed. However, due to violation of the abovementioned transfer assumption, the known true input WUE did not yield the known true input partitioning. This could only be achieved after introducing correction factors for the transfer assumption, which were known however only in the special case of the LES experiments.