Estimating and Validating Soil Evaporation and Crop Transpiration During the HiWATER-MUSOEXE
作者:Song, LS (Song, Lisheng)[ 1 ] ; Liu, SM (Liu, Shaomin)[ 1 ] ; Zhang, X (Zhang, Xi)[ 1 ] ; Zhou, J (Zhou, Ji)[ 2 ] ; Li, MS (Li, Mingsong)[ 2 ]
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷: 12  期: 2  页: 334-338
DOI: 10.1109/LGRS.2014.2339360
出版年: FEB 2015

摘要
The two-source energy balance (TSEB) model was successfully applied to estimate evaporation (E), transpiration (T), and evapotranspiration (ET) for land covered with vegetation, which has significantly important applications for the terrestrial water cycle and water resource management. However, the current composite temperature separation approaches are limited in their effectiveness in arid regions. Moreover, E and T are difficult to measure on the ground. In this letter, the ground-measured soil and canopy component temperatures were used to estimate E, T, and ET, which were better validated with observed ratios of E (E/ET%) and T (T/ET%) using the stable oxygen and hydrogen isotopes, and the ET measurements using an eddy covariance (EC) system. Our results indicated that even under the strongly advective conditions, the TSEB model produced reliable estimates of the E/ET% and T/ET% ratios and of ET. The mean bias and root-mean-square error (RMSE) of E/ET% were 1% and 2%, respectively, and the mean bias and RMSE of T/ET% were -1% and 2%, respectively. In addition, the model exhibited relatively reliable estimates in the latent heat flux, with mean bias and RMSE values of 31 and 61 W center dot m(-2), respectively, compared with the measurements from the EC system. These results demonstrated that a robust soil and vegetation component temperature calculation was crucial for estimating E, T, and ET. Moreover, the separate validation of E/ET% and T/ET% provides a good prospect for TSEB model improvements.
通讯作者地址: Song, LS (通讯作者)
Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.
地址:
[ 1 ] Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
[ 2 ] Univ Elect Sci & Technol China, Sch Resources & Environm, Chengdu 611731, Peoples R China