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- W3193562989 abstract "• Simple contextual model is attractive for the estimation of evapotranspiration (ET). • An operational new parameterization scheme based on feature space is proposed. • The scale dependencies are investigated by boundary parameters and ET performance. • The proposed method is superior to traditional method and has temporal continuity. • Large-scale ET distributions are obtained and are consistent with other products. A recent review has suggested relatively simple contextual models would remain attractive in the estimation of evapotranspiration (ET). The surface temperature-vegetation index feature space model is a typical representative since it provides direct monitoring of ET using simply and effective contextual information. However, the temporally continuous estimation and large-scale application issues are not well identified at previous studies. Under this background, the main motivation for this study is to develop an operational new parameterization scheme within the feature space framework for large-scale temporally continuous ET estimation. Specifically, the spatial domain division strategy was first designed to obtain the optimal grid division size for large-scale ET estimation. The model boundaries of these sub-regions were parameterized using spatial domain based temporal domain information at seasonal scale. The applicability of new method was demonstrated over the entire contiguous United States (CONUS) in the year 2008 using Moderate Resolution Imaging Spectroradiometer (MODIS) and Global Land Surface Satellite (GLASS) products. The comparison between present method and traditional method indicates that the new parameterization scheme produced at different reference spatial domains has a slight accuracy improvement over the 14 FLUXNET sites. In addition, the new method holds unique advantages in its simplicity and continuity, especially superior in the temporally continuous estimation of ET over a large extended region. The validation results of 14 FLUXNET sites indicate the correlation coefficient ( r ), mean absolute error ( MAE ), root mean square error ( RMSE ) the mean bias ( B ) values for continuous estimation of daily ET were 0.62, 28.430 W/m 2 , 36.133 W/m 2 and −0.059, respectively. The comparison results with existing ET product also demonstrated the comparable of ET distribution and estimates. Meanwhile, the boundary parameters obtained at seasonal scale also enhanced the physical meanings of feature space model. Consequently, the new parameterization scheme proposed in this study can be regarded as a suitable tool to provide large-scale temporally continuous estimation of ET." @default.
- W3193562989 created "2021-08-30" @default.
- W3193562989 creator A5021658618 @default.
- W3193562989 creator A5031590177 @default.
- W3193562989 date "2021-11-01" @default.
- W3193562989 modified "2023-10-13" @default.
- W3193562989 title "An operational parameterization scheme of surface temperature-vegetation index contextual model for large-scale temporally continuous evapotranspiration estimation: The case study of contiguous United States" @default.
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- W3193562989 doi "https://doi.org/10.1016/j.jhydrol.2021.126805" @default.
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