Estimating spatiotemporal dynamics of evapotranspiration and assessing the cause for its increase in China

Evapotranspiration (E) is a key flux on terrestrial surfaces connecting water-carbon cycle changes to environ-mental variabilities. Due to forcing data uncertainties, model structure complexities, and attribution method biases, the responses of E to environmental changes are poorly understood. In this study, we used a combined model based on the optimality principle to estimate 0.1 degrees monthly E values and the components of E in China from 1982 to 2018. This model was independently tested with flux tower and basin-scale water balance, showing a predictive performance comparable to other models. The modeling result indicates that, in China, the average weighted mean annual E was 397.90 mm yr(-1), of which 46.60% came from transpiration (Ec), 43.04% came from soil evaporation (Es) and 9.53% came from canopy interception evaporation (Ei). The growth in E (1.33 mm yr(-2)) was mainly caused by the increased Ec (78.95%), followed by the increased Es (21.05%). We further found that precipitation was the largest contributor to E, which primarily controlled the northwest E trends. The air temperature and net radiation mainly regulated the southern E trends. The leaf area index (LAI) dictated the E variations over central China. Although the LAI-induced increase in E (17%) could be offset by the CO2-induced decrease in E (13%), these contributing factors had different trends along an aridity index gradient. We highlight the divergent driving pattern of water, energy and vegetation in shaping E, which can support water resource planning and management.

Automated summary

In this study, a combined model based on the optimality principle was used to estimate monthly evapotranspiration (E) values and its components in China from 1982 to 2018. The modeling results showed that the average annual E in China was 397.90 mm yr(-1), with major contributions from transpiration (Ec), soil evaporation (Es), and canopy interception evaporation (Ei). Precipitation, air temperature, and net radiation were identified as the primary drivers of E trends in different regions of China. The findings emphasize the importance of considering the divergent driving patterns of water, energy, and vegetation for water resource planning and management.