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ARS Home » Pacific West Area » Riverside, California » Agricultural Water Efficiency and Salinity Research Unit » Research » Publications at this Location » Publication #341342

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: Flux variance partitioning: a new approach to advance eddy covariance observations for greenhouse gas emissions

item Anderson, Raymond - Ray
item Wang, Dong
item Skaggs, Todd
item Alfieri, Joseph
item Kustas, William - Bill

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 10/22/2017
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Eddy covariance (EC) is a well-established, non-intrusive observational technique that has long been used to measure the net carbon balance of numerous ecosystems including crop lands for perennial crops such as orchards and vineyards, and pasturelands. While EC measures net carbon fluxes well, it cannot directly observe component fluxes of the carbon cycle including Gross Primary Production (GPP) and Respiration (Re) and therefore must be combined with other approaches to estimate photosynthesis and respiration changes in response to management strategies. Most approaches to EC flux partitioning involve parameterizing Re as function of nighttime temperature and extrapolating to estimate daytime Re or parameterizing GPP as a light response function. Both of these approaches have significant potential weaknesses especially with determining GPP and Re under extreme or unusual environmental conditions. In this talk, we present a relatively novel approach to carbon flux partitioning, the flux variance partitioning method (FVP), which combines leaf level water use efficiency with high frequency CO2 and H2O observations to partition net carbon flux into GPP and Re. We apply FVP to multiple EC sites with different orchard cropping systems including drip-irrigated pistachios with and without a winter intercrop and a furrow irrigated peach orchard. We test the FVP model against existing approaches including nighttime Re and daytime light-GPP parameterizations. Results from the peach orchard show a strong potential for flux variance partitioning, but with larger differences in approaches for Re compared to GPP. The results indicate that the FVP method can provide a complimentary approach to existing light and temperature based parameterizations for partitioning EC fluxes.