## 3 Temperature-Based ET Models: Advantages, Drawbacks, and Evolution of Research
### Two-Source Surface Energy Balance Models
#### 3.2.1 The Two-Source Energy Balance Model (TSEB)  
A two-source model Energy Balance model, standing for TSEB, incorporating directional radiometric surface temperature was developed and validated using field measurements. It showed promise in predicting soil, sensible, and latent heat flux, with an acceptable agreement for most observations [20].  
The TSEB model was tested in Italy (Sicily), and the results were compared with the outputs of the agro-hydrological SWAP model. SWAP and TSEB showed slightly good agreement in some fields, with further investigations planned [60]. A study compared the accuracy of the TSEB and METRIC models in detecting crop water needs through ET. Both models performed similarly at fine and moderate scales, with METRIC exhibiting greater sensitivity in early growth and TSEB showing slightly greater sensitivity at maturity. Time integration of flux estimates improved daily ET estimates [61].  
The TSEB model was refined by incorporating ground measurements in irrigated maize and cotton fields, resulting in the TSEB-A model (considering the advective conditions). TSEB-A demonstrated improved agreement between observed and modeled soil and vegetation temperatures, accurately estimating ET in arid/semi-arid climates [62].  
For monitoring ET and aiding in irrigation planning, the TSEB model was compared to the FAO-56 dual approach. Both models performed well, with TSEB demonstrating smoother performance and potential for detecting water stress. TSEB was recommended for mapping ET on a large scale and supporting irrigation scheduling decisions [63]. In semiarid and arid regions, TSEB is suitable for estimating surface fluxes but tends to underestimate sensible heat flux and overestimate latent heat flux. A study introduced a new soil resistance formulation in TSEB, which showed improved accuracy in flux estimation without calibration or parameter tuning [64].  
To address complex tree-grass ecosystems (TGEs), the TSEB model was modified into the TSEB-2S model, considering phenological dynamics and dominant vegetation for different seasons. The adapted model significantly reduced errors in latent heat measurements compared to the default TSEB model [65]. For accurate ET modeling in TGEs, the impact of pixel heterogeneity was examined. The TSEB model performed well at <5 m resolution but had increased uncertainty at >10 m resolution. Incorporating landscape roughness or using a seasonally changing TSEB model improved performance for mixed pixels [66].  
Incorporating the original TSEB model with near-surface soil moisture, the TSEB-SM model improved the agreement with observed fluxes and showed advantages over TSEB, especially when the ratio of evapotranspiration was lower. It provided valuable insights into the global water cycle and showed potential as an alternative to complex Global Climate Models [67]. In another study, to estimate ET and plant transpiration (T), the TSEB-SIF model utilized sun-induced chlorophyll fluorescence (SIF) data. It outperformed the TSEB model in estimating ET, accurately partitioning T from ET under water deficit conditions [68].  
ET estimation using the TSEB model has demonstrated its effectiveness in yielding favorable outcomes when compared to field measurements. Nevertheless, recommendations for enhancing the precision of the soil heat flux formulations have been proposed. Several investigations have attested to the preference for TSEB in scenarios when data are plenty available. Moreover, it is important to use TSEB, bearing in mind its temporal sensitivities, which exhibit seasonally dependent variations.