A method to correct eddy covariance flux underestimates under an advective environment for arid or semi-arid regions

Water scarcity is one of the main factors limiting agricultural development in arid or semi-arid areas. Accurate Evapotranspiration (ET) observations and estimations are crucial in water cycle studies to estimate water losses from the terrestrial surfaces to the atmosphere to close the regional water budget. The eddy covariance (EC) method is an important technique measure ET and other land surface energy fluxes. However, the underestimation of energy fluxes and the problem of EC energy balance non-closure are far from solved. In this study, a new method is proposed to account for advection in order to correct EC data under advective environments. This advection based method was applied to data from Bushland, TX, which is subject to dry air and strong winds. Observations from two identical EC systems as well as two precision monolithic weighing lysimeters were used in this analysis. Both EC sites showed significant underestimates of evapotranspiration (ET) compared with lysimeter measurements. The daily energy balance closure for NE01 and SE02 sites were 0.78 and 0.74 respectively. The advection correction method provided improved performance in daytime, and it is more suitable for ET estimate than forcing closure under the advective environment. For nighttime, two methods (NCM1 and NCM2) were proposed to correct EC underestimates. Finally, all the corrected ET values were compared with the lysimeter measurements. For NE01 site, the MAD (mean absolute deviation) and the RMSD (root mean square deviation) were 47.72 W/m² and 67.66 W/m², respectively; and the r² (coefficient of determination) was 0.85. For SE02 site, the MAD and RMSD were 30.59 W/m² and 44.43 W/m²; and the r² was 0.93. The statistical measures illustrated that the proposed methods are functional and appropriate under an advective environment. The accurate estimate of actual evapotranspiration will benefit both the strategic planning of optimal water uses and the improved understanding the environmental and hydrological processes.