Editorial Type:
Article
Article Type:
Research Article

Partitioning Evapotranspiration into Soil Evaporation and Canopy Transpiration via a Two-Source Variational Data Assimilation System

Tongren Xu State Key Laboratory of Remote Sensing Science, Research Center for Remote Sensing and GIS, and School of Geography, Beijing Normal University, Beijing, China

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Sayed M. Bateni Department of Civil and Environmental Engineering, and Water Resources Research Center, University of Hawai‘i at Mānoa, Honolulu, Hawaii

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Steven A. Margulis Department of Civil and Environmental Engineering, University of California Los Angeles, Los Angeles, California

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Lisheng Song State Key Laboratory of Remote Sensing Science, Research Center for Remote Sensing and GIS, and School of Geography, Beijing Normal University, Beijing, China

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Shaomin Liu State Key Laboratory of Remote Sensing Science, Research Center for Remote Sensing and GIS, and School of Geography, Beijing Normal University, Beijing, China

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Ziwei Xu State Key Laboratory of Remote Sensing Science, Research Center for Remote Sensing and GIS, and School of Geography, Beijing Normal University, Beijing, China

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Print Publication:
01 Sep 2016
DOI:
https://doi.org/10.1175/JHM-D-15-0178.1
Page(s):
2353–2370
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Abstract

The primary objective of this study is to assess the accuracy of the two-source variational data assimilation (TVDA) system for partitioning evapotranspiration (ET) into soil evaporation (ETS) and canopy transpiration (ETC). Its secondary aim is to compare performance of the TVDA system with the commonly used two-source surface energy balance (TSEB) method. A combination of eddy-covariance-based ET observations and stable-isotope-based measurements of the ratio of evaporation and transpiration to total evapotranspiration (ETS/ET and ETC/ET) over an irrigated cropland site (the so-called Daman site) in the middle reach of the Heihe River basin (northwestern China) was used to investigate these objectives. The results indicate that the TVDA method predicts ETS and ETC more accurately than TSEB. Root-mean-square errors (RMSEs) of midday (1300–1500 LT) averaged soil and canopy latent heat flux (LES and LEC) estimates from TVDA are 23.1 and 133.0 W m−2, respectively. Corresponding RMSE values from TSEB are 41.9 and 156.0 W m−2. Compared to TSEB, the TVDA method takes advantage of all of the information in land surface temperature observations in the estimation period by leveraging a dynamic model (the heat diffusion equation) and thus can generate more accurate LES and LEC estimates.

Corresponding author address: Dr. Tongren Xu, School of Geography, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China. E-mail: xutr@bnu.edu.cn

Abstract

The primary objective of this study is to assess the accuracy of the two-source variational data assimilation (TVDA) system for partitioning evapotranspiration (ET) into soil evaporation (ETS) and canopy transpiration (ETC). Its secondary aim is to compare performance of the TVDA system with the commonly used two-source surface energy balance (TSEB) method. A combination of eddy-covariance-based ET observations and stable-isotope-based measurements of the ratio of evaporation and transpiration to total evapotranspiration (ETS/ET and ETC/ET) over an irrigated cropland site (the so-called Daman site) in the middle reach of the Heihe River basin (northwestern China) was used to investigate these objectives. The results indicate that the TVDA method predicts ETS and ETC more accurately than TSEB. Root-mean-square errors (RMSEs) of midday (1300–1500 LT) averaged soil and canopy latent heat flux (LES and LEC) estimates from TVDA are 23.1 and 133.0 W m−2, respectively. Corresponding RMSE values from TSEB are 41.9 and 156.0 W m−2. Compared to TSEB, the TVDA method takes advantage of all of the information in land surface temperature observations in the estimation period by leveraging a dynamic model (the heat diffusion equation) and thus can generate more accurate LES and LEC estimates.

Corresponding author address: Dr. Tongren Xu, School of Geography, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China. E-mail: xutr@bnu.edu.cn
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