不同下垫面DTD模型与TSEB模型比较

双源能量平衡模型（Two Source Energy Balance, TSEB）和双温度差模型（Dual Temperature Difference, DTD）目前已应用于不同的下垫面类型和环境条件下地表蒸散发估算研究,但是由于模型构建理论机理的差异,模型表现会随着下垫面类型和环境条件的变化而有所不同。因此,本研究选取了黑河流域高寒草地、半干旱区灌溉农田以及干旱区河岸林3种下垫面类型地面观测数据,系统分析了DTD模型和TSEB模型的适用性以及主要误差来源。结果表明:① 在瞬时尺度上,DTD模型在高寒草地上估算潜热通量的误差较小,其RMSE为62.00 W/m²,而TSEB模型的RMSE为75.49 W/m²,2个模型的精度会随着植被覆盖度的增加而出现差异;在半干旱区灌溉农田区域,2种模型表现较为一致,但是在干旱区河岸林,2种模型都低估了潜热通量,且模型误差较大;② 在日尺度上,DTD模型和TSEB模型的表现与瞬时尺度表现较为一致,同时2种模型拆分的植被蒸腾比与基于uWUE模型（Water Use Efficiency, uWUE）拆分的结果吻合较好,但DTD模型的表现要优于TSEB模型;③ 相比较DTD模型而言,TSEB模型对地表温度输入误差更为敏感。本研究通过对比DTD模型和TSEB模型在不同下垫面和环境条件的表现,为今后模型优化提供了理论依据。

Evaluating Two Source Energy Balance and Dual Temperature Difference Models under Various Landcovers and Environment Conditions

Operational application of an appropriate model to estimate evapotranspiration (ET) and the components evaporation (E), transpiration (T) at a range of space and time scales is very useful for managing water resources. The Two Source Energy Balance (TSEB) and Dual Temperature Difference (DTD) models have been applied to estimate land surface evapotranspiration under various landcover types and environment conditions. The DTD model requires twice radiometric temperature observations as inputs while the TSEB model only use single observation. This may reduce the uncertainty of DTD model which introduced from the observation or remotely sensed based radiometric temperatures. However, the two models may perform inconsistent under various land surface, which mainly associated with the different theoretical mechanisms in the models. In this study, the two models were evaluated using the long time ground observation data collected from three total different landcover types and environment conditions, including alpine grassland, semi-arid irrigated farmland and arid riparian forest in Heihe River Basin in Northwest China. The results showed that the latent heat flux estimated by the DTD model had a better agreement with half an hour ground measurements at the alpine grassland site, with the RMSE value of 62.00 W/m^2, while TSEB model showed a higher RMSE value of 75.49 W/m². But the performance of the two models was associated with the variation of the vegetation coverage. While, in the semi-arid farmland site, the performances of two models were more consistent where they produced a closer RMSE values, but in the arid riparian forest site, both of the models significantly underestimated the latent heat flux. The DTD model showed a worse agreement with the ground measurements in both sensible and latent heat fluxes. The DTD modeled latent heat flux had a higher RMSE values of 136.74 W/m² where the TSEB model had a RMSE value of 86.40 W/m². The better agreement of the TSEB model latent heat fluxes may associate with greater underestimation of modeled sensible heat flux which can partly compensate underestimation of net radiation. However, at the daily scale the performances of the DTD model and TSEB model were more similar. Additionally, the ratio of plant transpiration to evapotranspiration partitioned by the two models were in good agreement with results simulated from water use efficiency (uWUE) model with ground measurements, while the DTD model also performed better than the TSEB model. Finally, the TSEB model was more sensitive to the model input of land surface temperature. Therefore how to improve the accuracy of remote sense land surface temperature products is vital to the model application. Meanwhile, future researches can focus on optimizing model for extending applications over heterogeneous surface and different meteorological conditions.