Assessment of Multi-Source Evapotranspiration Products over China Using Eddy Covariance Observations

As an essential variable in linking water, carbon, and energy cycles, evapotranspiration (ET) is difficult to measure. Remote sensing, reanalysis, and land surface model-based ET products offer comprehensive alternatives at different spatio-temporal intervals, but their performance varies. In this s...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2018-11, Vol.10 (11), p.1692
Main Authors: Li, Shijie, Wang, Guojie, Sun, Shanlei, Chen, Haishan, Bai, Peng, Zhou, Shujia, Huang, Yong, Wang, Jie, Deng, Peng
Format: Article
Language:English
Subjects:
a stratification method
Accuracy
Algorithms
Carbon cycle
China
Climate change
Covariance
Criteria
Data collection
Ecosystems
eddy covariance observations
Energy
Estimates
Evaporation
Evapotranspiration
Humidity
Hydrology
Irrigation
Laboratories
latent heat flux
multi-source
Precipitation
Remote sensing
Stratification
Vortices
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Summary:As an essential variable in linking water, carbon, and energy cycles, evapotranspiration (ET) is difficult to measure. Remote sensing, reanalysis, and land surface model-based ET products offer comprehensive alternatives at different spatio-temporal intervals, but their performance varies. In this study, we selected four popular ET global products: The Global Land Evaporation Amsterdam Model version 3.0a (GLEAM3.0a), the Modern Era Retrospective-Analysis for Research and Applications-Land (MERRA-Land) project, the Global Land Data Assimilation System version 2.0 with the Noah model (GLDAS2.0-Noah) and the EartH2Observe ensemble (EartH2Observe-En). Then, we comprehensively evaluated the performance of these products over China using a stratification method, six validation criteria, and high-quality eddy covariance (EC) measurements at 12 sites. The aim of this research was to provide important quantitative information to improve and apply the ET models and to inform choices about the appropriate ET product for specific applications. Results showed that, within one stratification, the performance of each ET product based on a certain criterion differed among classifications of this stratification. Furthermore, the optimal ET (OET) among these products was identified by comparing the magnitudes of each criterion. Results suggested that, given a criterion (a stratification classification), the OETs varied among stratification classifications (the selected six criteria). In short, no product consistently performed best, according to the selected validation criterion. Thus, multi-source ET datasets should be employed in future studies to enhance confidence in ET-related conclusions.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs10111692