Evaluating the complementary relationship for estimating evapotranspiration using the multi-site data across north China

The ability to predict actual evapotranspiration flux (λEa) by physically based evaporanspiration (ET) model is limited globally due to the difficulty in validating the site-specific model parameters. Thus, the approaches for estimating λEa using only routine meteorological variables play a critical role in understanding and predicting hydrological cycle in the context of climate change. In this study, the performance of a complementary relationship (CR) method (Granger and Gray, 1989; GG model) on different timescales (daily and half-hourly) was evaluated using a high-quality dataset of selected 12 eddy covariance flux towers, which encompassed a number of cropland, grassland, evergreen needleleaf forest, desert shrub and wetland sites across northern China. The results indicated that the GG model is applicable in estimating daily λEa for most ecosystems across northern China. However, significant underestimations of daily λEa were found for the croplands (Daman and Dunhuang sites) and the desert shrub (Ejina) in the arid northwest China, which may be attributed to the enhanced λEa by horizontal advection and the deep root water-uptake, respectively. By using the Monin-Obukhov similarity theory with a surface energy balance constraint, the model performance on half-hourly timescale was satisfactory for the 12 tower sites with R2 ranging from 0.54 to 0.81 and the slopes of Deming regression line between measured and simulated λEa from 0.77 to 1.14. Indeed, the study highlights the need for further investigation of the timescale dependence of the CR-based ET models.