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Assessing human-induced evapotranspiration change based on multi-source
data and Bayesian model averaging at the basin scale
1 1，2 3 4 1 1
WEI Lin ，DUAN Kai ，LIU Xiaodong ，LIN Yuru ，CHEN Xiaohong ，WANG Xiaola
（1. College of Civil Engineering， Sun Yat - Sen University， Guangzhou 510275， China；
2. Southern Marine Science and Engineering Guangdong Laboratory（Zhuhai），Zhuhai 519082，China；
3. College of Forestry and Landscape Architecture， South China Agricultural University， Guangzhou 510642， China；
4. Changjiang River Scientific Research Institute， CWRC， Wuhan 430010， China）
Abstract： Anthropogenic disturbance on terrestrial evapotranspiration intensifies with socioeconomic develop⁃
ments. However，on-site evapotranspiration measurement is not readily available in many areas，and the ap⁃
plicability of data from large-scale land surface models and remote-sensing products is restrained by chal⁃
lenges in resolution gaps and spatial heterogeneity. In this paper， an evaluation framework of human-in⁃
duced evapotranspiration change based on multi-source data and the Bayesian model averaging method is
proposed. The case study in the Pearl River basin of China indicates that the reliability of assessment can
be significantly improved by assimilating datasets derived from ground observations （precipitation， stream⁃
flow）， water census， remote-sensing （GRACE satellite）， and land surface models （Noah， CLSM， VIC，
ERA-Interim）， and synthesizing outputs from individual models in a probabilistic way. The results show
that mean annual evapotranspiration was enhanced by 21% （137 mm/a） by human activities during
2003-2016， with the maximum and minimum impact found in May （+38 mm/month） and July （-27 mm/
month）， respectively. Irrigation water consumption and reservoir regulation were likely to be the major fac⁃
tors that dominated monthly variations in human-induced evapotranspiration change.
Keywords： evapotranspiration； human activity； multi-source data； Bayesian model averaging； the Pearl
River Basin
（责任编辑：耿庆斋）
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