Simultaneously assimilating multivariate data sets into the two-source evapotranspiration model by Bayesian approach: application to spring maize in an arid region of northwestern China

Abstract

Based on direct measurements of half-hourly canopy evapotranspiration (ET; W m−2) using the eddy covariance (EC) system and daily soil evaporation (E; mm day−1) using microlysimeters over a crop ecosystem in arid northwestern China from 27 May to 14 September in 2013, a Bayesian method was used to simultaneously parameterize the soil surface and canopy resistances in the Shuttleworth–Wallace (S–W) model. Four of the six parameters showed relatively larger uncertainty reductions (> 50%), and their posterior distributions became approximately symmetric with distinctive modes. There was a moderately good agreement between measured and simulated values of half-hourly ET and daily E with a linear regression being y = 0.84 x + 0.18 (R2 = 0.83) and y = 1.01 x + 0.01 (R2 = 0.82), respectively. The causes of underestimations of ET by the S–W model was possibly attributed to the microscale advection, which can contribute an added energy in the form of downward sensible heat fluxes to the ET process. Therefore, the advection process should be taken into account in simulating ET in heterogeneous land surfaces. Also, underestimations were observed on or shortly after rainy days, which may be due to direct evaporation of liquid water intercepted in the canopy. Thus, the canopy interception model should be coupled to the S–W model in the long-term ET simulation.