Evaluation of Six Satellite-Based Terrestrial Latent Heat Flux Products in the Vegetation Dominated Haihe River Basin of North China

In this study, six satellite-based terrestrial latent heat flux (LE) products were evaluated in the vegetation dominated Haihe River basin of North China. These LE products include Global Land Surface Satellite (GLASS) LE product, FLUXCOM LE product, Penman-Monteith-Leuning V2 (PML_V2) LE product, G...

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Bibliographic Details
Published in:Forests 2021-12, Vol.12 (12), p.1632
Main Authors: Li, Yufu, Sui, Xinxin, Yao, Yunjun, Cheng, Haixia, Zhang, Lilin, Wang, Lu, Ning, Jing, Shang, Ke, Yang, Junming, Yu, Ruiyang, Liu, Lu, Guo, Xiaozheng, Xie, Zijing
Format: Article
Language:English
Subjects:
Algorithms
Datasets
eddy covariance
Evaporation
Evapotranspiration
Fluctuations
Haihe River basin
Heat flux
Heat transfer
Latent heat
Machine learning
Methods
Remote sensing
River basins
Rivers
Root-mean-square errors
satellite
Satellites
Spectroradiometers
Terrestrial environments
terrestrial latent heat flux
Vegetation
Water balance
water balance method
Water budget
Water resources
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Summary:In this study, six satellite-based terrestrial latent heat flux (LE) products were evaluated in the vegetation dominated Haihe River basin of North China. These LE products include Global Land Surface Satellite (GLASS) LE product, FLUXCOM LE product, Penman-Monteith-Leuning V2 (PML_V2) LE product, Global Land Evaporation Amsterdam Model datasets (GLEAM) LE product, Breathing Earth System Simulator (BESS) LE product, and Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD16) LE product. Eddy covariance (EC) data collected from six flux tower sites and water balance method derived evapotranspiration (WBET) were used to evaluate these LE products at site and basin scales. The results indicated that all six LE products were able to capture the seasonal cycle of LE in comparison to EC observations. At site scale, GLASS LE product showed the highest coefficients of determination (R2) (0.58, p < 0.01) and lowest root mean square error (RMSE) (28.2 W/m2), followed by FLUXCOM and PML products. At basin scale, the LE estimates from GLASS product provided comparable performance (R2 = 0.79, RMSE = 18.8 mm) against WBET, compared with other LE products. Additionally, there was similar spatiotemporal variability of estimated LE from the six LE products. This study provides a vital basis for choosing LE datasets to assess regional water budget.
ISSN:1999-4907
1999-4907
DOI:10.3390/f12121632