Complementary‐Relationship‐Based Modeling of Terrestrial Evapotranspiration Across China During 1982–2012: Validations and Spatiotemporal Analyses

蒸散量 环境科学 涡度相关法 中国 风速 短波辐射 气候学 植被(病理学) 大气科学 水文学(农业) 自然地理学 地理 气象学 生态系统 地质学 辐射 生物 物理 病理 考古 医学 岩土工程 量子力学 生态学
作者
Ning Ma,József Szilágyi,Yinsheng Zhang,Wenbin Liu
出处
期刊:Journal Of Geophysical Research: Atmospheres [Wiley]
卷期号:124 (8): 4326-4351 被引量:274
标识
DOI:10.1029/2018jd029850
摘要

Abstract Having recognized the limitations in spatial representativeness and/or temporal coverage of (i) current ground ET a observations and (ii) land surface model‐ and remote sensing‐based ET a estimates due to uncertainties in soil and vegetation parameters, a calibration‐free nonlinear complementary relationship (CR) model is employed with inputs of air and dew‐point temperature, wind speed, and net radiation to estimate 0.1°, monthly ET a over China during 1982–2012. The modeled ET a rates were first validated against 13 eddy‐covariance measurements, producing Nash‐Sutcliffe efficiency values in the range of 0.72–0.94. On the basin scale, the modeled ET a values yielded a relative bias of 6%, and a Nash‐Sutcliffe efficiency value of 0.80 in comparison with water‐balance‐derived evapotranspiration rates across 10 major river basins in China, indicating the CR‐simulated ET a rates reliable over China. Further evaluations suggest that the CR‐based ET a product is more accurate than seven other mainstream ET a products. The 31‐year mean annual ET a value decreases from the southeast to the northwest in China, resulting in a country average of 406 ± 15 mm/year. The country‐representative annual ET a rates slightly decreased with a rate of −0.5 mm/year ( p = 0.86) during 1982–2012. Annual ET a increased significantly over most parts of western and northeastern China but decreased significantly in many regions of the North China Plain as well as in the eastern and southern coastal regions. The present CR‐based method, with its calibration‐free nature and minimal data requirement, could help future calibrations/verifications of the more complex and more data‐intensive land surface model‐ and remote sensing‐based models.
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