## 3 Results and Discussion
### Remote Sensing Applications
#### 3.4.4 Water Management
[85], in turn, sought to improve irrigated agricultural productivity in northern Victoria by using a bio-economic modeling framework. Their study revealed that optimizing water efficiency, achieved through genetic improvement and precision water management, along with accessing 50% of available groundwater, had the greatest potential to maximize irrigated agricultural gross margins. [PERSON] et al. [86] compared tabulated crop coefficients to RS equivalents for monitoring irrigation water use. Localized tabulated coefficients, particularly for Australia, outperformed crop-specific RS equivalents, which struggled to match North American relationships. The study suggests that, overall, using localized tabulated crop coefficients is more effective in monitoring irrigation water use. [PERSON] et al. [87] used RS to quantify irrigation water use in remote areas, employing FAO56-based soil water deficit modeling. Their results revealed close agreement between metered irrigation time series and modeling, with only minor variations. Monte Carlo uncertainty analysis on RAW showed substantial improvements, ranging from 3% to 15% monthly and 56% to 68% annually, compared to studies neglecting soil water deficits. [PERSON] et al. [88] developed a study on almond crop water use under diverse irrigation treatments and surface energy balance algorithms. Data from a central California almond orchard was used, showing TSEB2 + S3 provided the most accurate evapotranspirationestimates. The results show that deficit irrigation strategies could save up to 37% of water without significantly reducing crop yield. In relation to other types of studies concerning different topics, four studies were conducted using a satellite platform. [PERSON] et al. [89] employed RS to analyze how water and salt stresses affect diverse crops in real agricultural conditions. Using the Sentinel-2 satellite system, the study revealed varied crop responses to salt and drought stress, considering factors such as crop type, growing season, and stress timing. [PERSON] et al. [10] studied the water-energy-food nexus in the California Central Valley, providing insights into regional precipitation and actual ET. [PERSON] [90] enhanced crop models and evaluated agricultural drought effects, revealing correlations between soil moisture, precipitation, and almond crop yields. [PERSON] et al. [91] proposed a new methodology for agricultural water management, demonstrating reduced water use and increased crop yield compared to traditional approaches. Two studies using MAV platforms focused on intra-crown temperature in almond trees and its correlation with water status. [PERSON] et al. [92] used a thermal infrared sensor on an aircraft, demonstrating a strong correlation between mean canopy temperature, stomatal conductance, and SWP. [PERSON] et al. [93] studied solar-induced chlorophyll fluorescence (SIF) and CWSI variability in tree crowns under different water stress levels, providing insights into leaf physiological measures. Four studies using MAV platforms addressed various topics. [PERSON] et al. [18] examined intra-tree structural variation and its correlation with CWSI and stomatal conductance. [PERSON] and [PERSON] [94] assessed turbulent fluxes over an almond orchard using three RS-based models, with SEBAL demonstrating the highest overall performance. [PERSON] et al. [95] used the SCOPE model to measure the maximum carboxylation rate (Vcmax) as an indicator of photosynthetic rate reductions under stress. [PERSON] et al. [96] detected diurnal variations in fruit orchard canopy water content using a MSP and TIR MAV sensor. Five studies using UAVs focused on water stress monitoring in almond orchards. [PERSON] et al. [97] presented a framework for processing high-resolution MSP imagery based on PCA for quantifying crop stress, showing a significant correlation between the first principal component and SWP. [PERSON] et al. [7] evaluated UAV-based indicators for early water stress detection in four almond cultivars, emphasizing the sensitivity of CWSI compared to NDVI.