## 1 Introduction  
Evapotranspiration (ET) is a critical component of the hydrological cycle, deeply influencing water availability in ecosystems and agricultural landscapes [1]. Yet, predicting ET on a large scale is quite challenging, given the myriad of physical drivers at play. Factors such as wind patterns, cloud cover, soil moisture, surface albedo, precipitation, radiation scattering, and surface heterogeneity introduce considerable variability. Moreover, the intricate interplay of crop biophysical characteristics, including canopy structure, vegetation abundance, phenology, and energy partitioning, further compounds this variability. This complexity is especially pronounced in data-sparse regions and heterogeneous land use systems, such as the Mediterranean region [2]. This region experiences a complex interplay of factors, including diverse land cover, heterogeneous topography, and variable climatic conditions, making ET estimation particularly challenging [3]. Moreover, ET and precipitation are the principal mechanisms of the water balance in the Mediterranean Basin. Due to precipitation decline, Mediterranean ecosystems in specific arid and semi-arid production systems are more vulnerable to water stress leading to growing hydrological imbalances in the basin [4]. The accelerating near-surface temperatures and declining near-surface soil moisture exacerbate the need for precise ET assessments [5]. Our understanding of Mediterranean ecosystems' reactions to stressed hydro-climatological conditions is still limited. This information gap demands strong monitoring and modeling capabilities in terrestrial water flux quantification (evapotranspiration, runoff, and groundwater storage), especially ET, which is a principal water-extracting component in arid regions. ET's accurate quantification with precipitation is becoming critical in the basin with the growing water and food scarcity [6; 7]. Since many ET modeling schemes exist, it is meaningful to find the best approach for the Mediterranean region through which we can manage and control water stress, seasonal water shortages, and the expansion of irrigated agriculture. While various remote sensing and modeling approaches have been developed to estimate ET, their effectiveness in capturing the complexities of the Mediterranean region is still negotiable. Remote sensing-based models often rely on empirical relationships and simplifications, neglecting the influence of sub-surface hydrology and complex land use patterns. ET by these models is derived from the integration of radiometric land surface temperature (LST), and biophysical variables, i.e., leaf area index (LAI), photosynthetically active radiation (PAR), fractional vegetation cover (FVC), clumping index, leaf angles, canopy height, leaf abundance, ecosystem hierarchy, etc. [8; 9]. Some other techniques are based on net radiation and temperature differentials [10; 11], or an inferential approach constrained by crop coefficients [12; 13; 14]. These simple generic models do not account for the horizontal movement of soil energy fluxes and water and heat storage [15; 16; 17; 18]. Some examples are the Mapping ET at high Resolution with Internalized Calibration-Earth Engine Evapotranspiration Flux (METRIC-EEFlux), surface energy balance index (SEBI), Operational Simplified Surface Energy Balance (SSEBop), Atmosphere-Land Exchange Inverse algorithm (ALEXI), and Atmosphere Land Exchange Inverse Disaggregation algorithm (DisALEXI). In these models, LST is used as a proxy for soil moisture conditions of the upper soil layer. Surface resistances are modeled as a function of abstracted hydrology following the aerodynamic theory. The accurate estimation of aerodynamic resistance is crucial, due to complexities in atmospheric conditions and surface characteristics.