Determining the Isotopic Composition of Surface Water Vapor Flux From High-Frequency Observations Using Flux-Gradient and Keeling Plot Methods

Abstract

The isotopic composition of surface water vapor flux (δE) is a quantity frequently used to investigate the local and regional water cycle. This study reports the results of a comparative evaluation of δE determined with the Keeling plot and the flux-gradient methods using high-frequency data collected at a cropland site and a lake site. Three regression models, ordinary least squares (OLS), York's solution (YS), and geometric mean regression, were tested with the Keeling plot method. Results show that concentration-dependent field characterization of measurement errors can improve the estimation of the YS regression. For both sites, broad agreement was achieved among the Keeling plot method with YS regression, the Keeling plot method with OLS regression and the flux-gradient method. For the lake site, OLS was the least biased of the three regression models in reference to the δE calculated by the Craig-Gordon (CG) model of isotopic evaporation of open water. Good agreement was aslo achieved between the flux-gradient method and the CG model at the lake site under open-fetch conditions. A footprint analysis suggests that the Keeling method with OLS regression may be less sensitive to fetch than the flux-gradient method.