Correlation-based flux partitioning of water vapor and carbon dioxide fluxes: Method simplification and estimation of canopy water use efficiency

• Published in: Agricultural and forest meteorology Vol. 279; no. C; p. 107732
• Main Authors: Scanlon, Todd M., Schmidt, Daniel F., Skaggs, Todd H.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.12.2019; Elsevier
• Subjects: canopy; carbon dioxide; deciduous forests; Eddy covariance; evaporation; Flux partitioning; growing season; photosynthesis; soil; time series analysis; transpiration; Water use efficiency; water vapor; Flux partitioning; Eddy covariance; Water use efficiency
• ISSN: 0168-1923; 1873-2240
• DOI: 10.1016/j.agrformet.2019.107732

•Simplified equations are developed to partition water vapor and CO2 fluxes.•Scalar statistics from high frequency time series are used as input.•An optimization-based approach is used to quantify vegetation water use efficiency.•The technique is demonstrated on eddy covariance data collected over a forest. The partitioning of water vapor and carbon dioxide (CO2) exchange between vegetation and the atmosphere remains a current research priority. A technique that has been proposed to simultaneously partition these fluxes, based on the correlation between their high-frequency concentration time series, has been the subject of recent empirical evaluations and theoretical advances. The method assumes that flux-variance similarity can be applied separately to stomatal exchange (transpiration for water vapor and net photosynthesis for CO2) and non-stomatal exchange (direct evaporation for water vapor and soil and stem respiration for CO2). Here, we present a mathematical simplification of this approach, from which the partitioned fluxes can be derived from routine eddy covariance measurements. The simplification arises from the fact that the transpiration and net photosynthesis fluxes are linearly related in solution space with respect to variable canopy water use efficiency, W. Conditions that are amenable to successful partitioning can now be determined a priori for a given averaging period. The simplified framework also has the benefit of providing a means for estimating W based on optimization theory. This allow for the estimation of W without any preconceptions of how the intercellular CO2 concentration, ci, varies as a function of ambient conditions. The simplified partitioning framework is applied to eddy covariance measurements collected over a mixed deciduous forests for three growing season. Aside from being more computationally efficient, the partitioned results exhibit less scatter compared with prior implementations.