Water Flux Partitioning for Eddy Covariance Data

Here we present an overview of methods for partitioning evapotranspiration (ET) from eddy covariance data. We focus on methods that are designed to use the core energy and carbon fluxes, as well as meteorological data, and do not require supplemental measurements or campaigns. A comparison of three such methods for estimating transpiration (T) showed high correlations between them (R² of  daily T between 0.80 and 0.87) and higher correlations to daily stand T estimates from sap flow data (R² between 0.58 and 0.66) compared to the tower ET (R2 = 0.49). However, the three methods show significant differences in magnitude, with T/ET values ranging from 45% to 77%. Despite the differences in magnitude, the methods show plausible patterns with respect to LAI, seasonal cycles, WUE, and VPD; moreover, they represent an improvement compared to using ET as a proxy for T even when filtering for days after rain. Finally, we outline practical aspects of applying the methods, such as how to apply the methods and code availability.