A Correlation-Based Flux Partitioning Method and Its Application to a Vineyard in California's Central Valley: A Case Study.

The persistent and ongoing California drought has not only tasked already-limited water resources, it has also hampered crop production and damaged the state’s economy. In order to minimize the adverse effects of drought and ensure the sustainability of California agriculture, policymakers, resource managers, and agricultural producers must maximize the effective use of the available water. Any efforts toward this goal are predicated on accurate information regarding crop water productivity, i.e. the fraction of the total evapotranspiration (ET) that contributes to crop yield expressed in terms of transpiration. While a number of approaches, such as isotope analysis and microlysimeter systems, have been developed to partition ET between soil evaporation (E) and transpiration (T), collecting reliable continuous measurements at field scales remains problematic. This study presents the application of a recently developed correlation-based technique that overcomes these difficulties by leveraging high frequency data measured via eddy covariance. Specifically, this scheme wavelet decomposition and the relationship between stomatal and non-stomatal moisture and carbon fluxes to separate E and T. The technique was evaluated over a drip-irrigated vineyard located in California’s Central Valley using data collected during the 2015 growing season as a part of the GRAPEX field campaign. The results indicate a clear diurnal pattern in the fraction of ET due to T with a mid-day peak averaging 80% during the growing season. Similarly, there is a strong seasonal trend with the fraction of ET due T increasing in proportion to the increasing vine biomass during the growing season; at its maximum T accounts for approximately 90% of the total moisture flux.