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Source Partitioning of H2O and CO2 Fluxes Based on High Frequency Eddy Covariance Data: a Comparison between Study Sites

Authors: Anne Klosterhalfen; Alexander Graf; Nicolas Brüggemann; Clemens Drüe; Odilia Esser; María P. González-Dugo; Günther Heinemann; +14 Authors

Source Partitioning of H2O and CO2 Fluxes Based on High Frequency Eddy Covariance Data: a Comparison between Study Sites

Abstract

Abstract. For an assessment of the role 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 the source partitioning approaches after Scanlon and Kustas (2010; SK10) and after Thomas et al. (2008; TH08) to high frequency eddy covariance measurements of twelve study sites including various ecosystems (croplands, grasslands, and forests) in a number of countries. 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 between turbulence characteristics, site characteristics (such as plant cover type, canopy height, canopy density and measurement height), and performance of the partitioning methods. We could identify characteristics of a data set as prerequisite for a sufficient 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 more irregular than of H2O fluxes. Results derived with SK10 showed relatively large dependencies on estimated water use efficiency (WUE) at leaf-level, which is needed as an input. Measurements of outgoing longwave radiation used for the estimation of foliage temperature and 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 other 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 and canopy height. The performance of TH08 was more dependent on canopy height and leaf area index. It was found, that all site characteristics which increase dissimilarities between scalars enhance partitioning performance for SK10 and TH08.

Countries
Netherlands, Germany, Germany, Germany, Germany, Germany
Keywords

Meteorologie en Luchtkwaliteit, Climate Change and Adaptive Land and Water Management, 550, Meteorology and Air Quality, Climate Change, Klimaatverandering en adaptief land- en watermanagement, Klimaatverandering, Life, QH501-531, Life Science, QH540-549.5, QE1-996.5, info:eu-repo/classification/ddc/550, WIMEK, Ecology, ddc:550, Alterra - Klimaatverandering en adaptief land- en watermanagement, Geology, Climate Resilience, Earth sciences, Klimaatbestendigheid, Alterra - Climate change and adaptive land and water management

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
21
Top 10%
Average
Top 10%
Green
gold