Source partitioning of H&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;O and CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; fluxes based on high-frequency eddy covariance data: a comparison between study sites

Anne Klosterhalfen,Marius Schmidt,Thomas Pütz,Nicolas Brüggemann,Mario Ramos Rodríguez,Odilia Esser,Alexander Graf,Matthias Mauder,Todd M Scanlon,Veronika Valler,Clemens Drüe,Günther Heinemann,Arnold F Moene,Corinna Rebmann,Patrizia Ney,Harry Vereecken,R Steinbrecher ,C.m.j Jacobs ,Matthias Zeeman ,M P González‐Dugo ,Christoph Thomas

doi:10.5194/bg-16-1111-2019

Abstract

Abstract. For an assessment of the roles of soil and vegetation in the climate system, a further understanding of the flux components of H2O and CO2 (e.g., transpiration, soil respiration) and their interaction with physical conditions and physiological functioning of plants and ecosystems is necessary. To obtain magnitudes of these flux components, we applied source partitioning approaches after Scanlon and Kustas (2010; SK10) and after Thomas et al. (2008; TH08) to high-frequency eddy covariance measurements of 12 study sites covering different ecosystems (croplands, grasslands, and forests) in different climatic regions. Both partitioning methods are based on higher-order statistics of the H2O and CO2 fluctuations, but proceed differently to estimate transpiration, evaporation, net primary production, and soil respiration. We compared and evaluated the partitioning results obtained with SK10 and TH08, including slight modifications of both approaches. Further, we analyzed the interrelations among the performance of the partitioning methods, turbulence characteristics, and site characteristics (such as plant cover type, canopy height, canopy density, and measurement height). We were able to identify characteristics of a data set that are prerequisites for adequate performance of the partitioning methods. SK10 had the tendency to overestimate and TH08 to underestimate soil flux components. For both methods, the partitioning of CO2 fluxes was less robust than for H2O fluxes. Results derived with SK10 showed relatively large dependencies on estimated water use efficiency (WUE) at the leaf level, which is a required input. Measurements of outgoing longwave radiation used for the estimation of foliage temperature (used in WUE) could slightly increase the quality of the partitioning results. A modification of the TH08 approach, by applying a cluster analysis for the conditional sampling of respiration–evaporation events, performed satisfactorily, but did not result in significant advantages compared to the original method versions developed by Thomas et al. (2008). The performance of each partitioning approach was dependent on meteorological conditions, plant development, canopy height, canopy density, and measurement height. Foremost, the performance of SK10 correlated negatively with the ratio between measurement height and canopy height. The performance of TH08 was more dependent on canopy height and leaf area index. In general, all site characteristics that increase dissimilarities between scalars appeared to enhance partitioning performance for SK10 and TH08.

Highlights

The eddy covariance (EC) method is a micrometeorological technique commonly used to measure the energy, water vapor, and carbon dioxide exchange between biosphere and atmosphere across a large range of scales in time and space (Baldocchi et al, 2001; Reichstein et al, 2012)
Or so-called source partitioning approaches can be applied to the net fluxes obtained with the EC method
Both approaches rely on the assumption that the presence of multiple sources and sinks in and below the canopy will lead to decorrelation of the high-frequency scalar concentrations measured by the EC method above the canopy

Summary

Introduction

The eddy covariance (EC) method is a micrometeorological technique commonly used to measure the energy, water vapor, and carbon dioxide exchange between biosphere and atmosphere across a large range of scales in time and space (Baldocchi et al, 2001; Reichstein et al, 2012). To estimate soil surface fluxes of both H2O and CO2 directly from highfrequency EC data without assumptions on such drivers, two distinct partitioning approaches were developed by Scanlon and coauthors (Scanlon and Sahu, 2008; Scanlon and Kustas, 2010) and Thomas et al (2008). Both approaches rely on the assumption that the presence of multiple sources and sinks in and below the canopy will lead to decorrelation of the high-frequency scalar concentrations measured by the EC method above the canopy. The scalar–scalar correlations of H2O and CO2 are, influenced by the sink–source distribution, and by height (atmospheric surface layer, roughness sublayer), surface heterogeneity (Williams et al, 2007), canopy density, and coherent structures (Edburg et al, 2012; Huang et al, 2013)

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