Numerical Investigation of Observational Flux Partitioning Methods for Water Vapor and Carbon Dioxide

Einara Zahn, Khaled Ghannam, Marcelo Chamecki, Arnold F. Moene, William P. Kustas, Stephen Good, Elie Bou-Zeid

Research output: Contribution to journalArticlepeer-review

Abstract

While yearly budgets of CO2 flux (Fc) and evapotranspiration (ET) above vegetation can be readily obtained from eddy-covariance measurements, the separate quantification of their soil (respiration and evaporation) and canopy (photosynthesis and transpiration) components remains an elusive yet critical research objective. In this work, we investigate four methods to partition observed total fluxes into soil and plant sources: two new and two existing approaches that are based solely 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 performances 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.

Original languageEnglish (US)
Article numbere2024JG008025
JournalJournal of Geophysical Research: Biogeosciences
Volume129
Issue number6
DOIs
StatePublished - Jun 2024

All Science Journal Classification (ASJC) codes

  • Forestry
  • Aquatic Science
  • Ecology
  • Water Science and Technology
  • Soil Science
  • Atmospheric Science
  • Palaeontology

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