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ARS Home » Pacific West Area » Riverside, California » Agricultural Water Efficiency and Salinity Research Unit » Research » Publications at this Location » Publication #344767

Research Project: Sustaining Irrigated Agriculture in an Era of Increasing Water Scarcity and Reduced Water Quality

Location: Agricultural Water Efficiency and Salinity Research Unit

Title: Fluxpart: Open source software for partitioning carbon dioxide and water vapor fluxes

Author
item Skaggs, Todd
item Anderson, Raymond - Ray
item Alfieri, Joseph
item Scanlon, T. - University Of Virginia
item Kustas, William - Bill

Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/16/2018
Publication Date: 2/27/2018
Citation: Skaggs, T.H., Anderson, R.G., Alfieri, J.G., Scanlon, T.M., Kustas, W.P. 2018. Fluxpart: Open source software for partitioning carbon dioxide and water vapor fluxes. Agricultural and Forest Meteorology. 253:218-224. https://doi.org/10.1016/j.agrformet.2018.02.019.
DOI: https://doi.org/10.1016/j.agrformet.2018.02.019

Interpretive Summary: The eddy covariance method is routinely used to measure gas fluxes over agricultural fields and other landscapes. Greater insight into the functioning of agroecosystems is possible if the measured gas fluxes can be separated into their constitutive components: the water vapor flux into transpiration and direct evaporation components, and the carbon dioxide flux into photosynthesis and respiration components. In this work, we present new mathematical results that facilitate partitioning analyses, and introduce new open source software that analyzes eddy covariance data streams and implements a partitioning algorithm. The research and software will benefit scientists, engineers, and irrigators seeking to monitor, understand, and optimize water use in agroecosystems.

Technical Abstract: The eddy covariance method is regularly used for measuring gas fluxes over agricultural fields and natural ecosystems. For many applications, it is desirable to partition the measured fluxes into constitutive components: the water vapor flux into transpiration and direct evaporation components, and the carbon dioxide flux into photosynthesis and respiration components. The flux variance similarity (FVS) partitioning method is based on flux variance similarity relationships and correlation analyses of high-frequency eddy covariance data. The FVS method is relatively complex computationally, and that complexity has likely been an impediment to greater use and testing of the procedure. In this work, we present a new algebraic solution to the key computational task in the partitioning algorithm, which significantly simplifies the FVS method. We also introduce Fluxpart, a free and open source Python 3 module that implements the FVS partitioning procedure. A few example flux partitioning calculations are presented.