Numerical Investigation of Observational Flux Partitioning Methods for
Water Vapor and Carbon Dioxide
Abstract
While yearly budgets of CO2 and evapotranspiration (ET) above forests
can be readily obtained from eddy-covariance measurements, the
quantification of their respective soil (respiration and evaporation)
and canopy (photosynthesis and transpiration) components remains an
elusive yet critical research objective. To this end, methods capable of
reliably partitioning the measured ET and F_c fluxes into their
respective soil and plant sources and sinks are highly valuable. In this
work, we investigate four partitioning methods (two new, and two
existing) that are based on analysis of conventional high frequency
eddy-covariance (EC) data. The physical validity of the assumptions of
all four methods, as well as their performance under different
scenarios, are tested with the aid of large eddy simulations, which are
used to replicate eddy-covariance field experiments. Our results
indicate that canopies with large, exposed soil patches increase the
mixing and correlation of scalars; this negatively impacts the
performance of the partitioning methods, all of which require some
degree of uncorrelatedness between CO2 and water vapor. In addition,
best performance for all partitioning methods were found when all four
flux components are non-negligible, and measurements are collected close
to the canopy top. Methods relying on the water-use efficiency (W)
perform better when W is known a priori, but are shown to be very
sensitive to uncertainties in this input variable especially when canopy
fluxes dominate. We conclude by showing how the correlation coefficient
between CO2 and water vapor can be used to infer the reliability of
different W parameterizations.