## 1 Introduction  
Irrigation for agriculture represents the most significant demand for freshwater uptake of around 70% of all water withdrawal [1; 2]. This demand is growing due to climate change. Increases in the intensity and frequency of droughts and heatwaves will affect soil water demand and supply of crops, hindering crop production [3; 4; 5]. Crops such as maize and soybean, sensitive to droughts, are already experiencing reductions in yields [6; 7; 8]. These staple crops are extensively grown for food production worldwide, covering areas of 139 million ha for maize and 75.5 million ha for soybean crops [9]. Thus, further information of their responses to droughts at the farm level can improve the sustainability of water use. In response to soil drought, or water stress, plants react with various physiological, biochemical, and morphological adjustments, observable early at the drought onset (fast changes) or after some time (slow changes) [10; 11]. Generally, as a result of soil drought, leaf water potential (\(\Psi_{\text{L}}\)) decreases and stomata close, which limits transpiration (T\({}_{\text{r}}\)) and photosynthesis (A) to different degrees depending on plant type, life history and environmental factors [12; 13; 14]. Thus, stomatal conductance (g\({}_{\text{s}}\)) is often used as an indirect proxy to detect plant water status and stress [12; 15; 16]. Cell enlargement is also a very sensitive process to mild water stress [11; 13], which it will be eventually reflected in lower canopy heights (h\({}_{\text{c}}\)) or leaf area index (LAI) [7; 17]. In addition, there are other delayed responses in pigments such as reductions in chlorophyll content [7; 10; 13; 18] or carotenoids [19]. Chlorophyll reduction caused by water stress can be attributed to chlorophyll degradation, pigment photo-oxidation, and insufficient synthesis of chlorophyll [17]. However, in the assessment of crop physiological responses to drought, it is not always easy to separate drought effects from phenology and leaf age effects [20]. Accounting explicitly for different hydraulic and metabolic traits is necessary to improve predictions to soil water stress. For example, maize plants have C\({}_{4}\) photosynthetic pathway, while soybean are classified as C\({}_{3}\), being less efficient under warm temperatures as their photorespiration is higher [21; 22]. Soil water stress could lead to more substantial declines of g\({}_{\text{s}}\) in C\({}_{3}\) species than C\({}_{4}\), due to metabolic limitations [23; 24]. In addition, species with more anisohydric behavior, as reported for maize [25] can delay stomatal closure, maintaining photosynthesis level. In contrast, more isohydric plants will rapidly close stomata in response to water deficit, limiting water stress damage but reducing CO\({}_{2}\) assimilation [16]. Incorporation of some of these different traits or responses in models (e.g., Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) [26; 27; 28], Light Use Efficiency Gross Primary Productivity (LUE GPP) [26; 29; 30] and Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) [31]) is key for better predictions and crop management. Remote sensing techniques have been widely used as a non-destructive approach to estimate plant biochemical and morphological constituents that modify energy absorption and scattering in different spectral wavelengths [20; 32; 33]. Relevant traits, such as hydraulic safety or photosynthetic pathways, can be detected through optical or thermal features [10; 34]. However, the use of remote sensing to estimate plant function or physiology is very complex, as the mechanisms linking reflectance and emission with plant functional gradients are not always explicit or known [35]. In remote sensing applications, the most frequent method to monitor plant responses to soil water stress is using vegetation indices (VIs) [10; 15; 36; 37].