## 3 Results and Discussion
### Remote Sensing Applications
#### 3.4.4 Water Management  
Water resource management is a critical global concern. Water plays a pivotal role in the production of food, energy, and sustaining health, while also being vital for providing potable water and ensuring sanitation [69]. Remote sensing platforms are progressively becoming integral to in situ monitoring networks due to their equipped sensors capable of conducting both direct and indirect measurements of various components within the hydrological cycle. Furthermore, these sensors offer crucial information for water management and enable the monitoring of the impact of hazards [70]. In this section, several  
Figure 11: Remote sensing platforms (**a**) implemented in studies health monitoring and disease detection studies along with the diseases identified (**b**). XF: Xylella Fastidiosa, OS: Ochre Spot, VD: Verticillium Dahlia. studies demonstrating the importance of RS platforms and sensors in water monitoring and management will be presented. Considering studies using the satellite platform, 12 studies associated with estimates of evapotranspiration (ET) were identified. [PERSON] et al. [71] applied the Simplified-Surface Energy Balance Index Algorithm (S-SEBI) to estimate ET in almond orchards, demonstrating reliable results with a low average root mean square error (RMSE) of 0.12 mm/h. [PERSON] et al. [72] used the Mapping ET at high resolution with the Internal Calibration (METRIC) technique for accurate daily and monthly ET estimates in a Californian almond orchard. [PERSON] and [PERSON] [73] studied crop water dynamics in the California Central Valley using Landsat-derived annual actual ET with the SSEBop model, revealing a substantial rise in almond cultivation area and water consumption. [PERSON] et al. [74] compared three RS ET models (pySEBAL, SEBS, and METRIC) for daily actual ET in almond orchards, showing generally acceptable agreement with in situ measurements. [PERSON] et al. [75] used the simplified Two-Source Energy Balance (STSEB) model to assess crop ET and related coefficients, aiding in predicting water needs based on orchard age and biophysical parameters. [PERSON] et al. [76] estimated actual ET and crop coefficients for almonds, revealing varying water stress coefficients (Ks) through regressions between CWSI and stem water potential (SWP). Another study by [PERSON] et al. [77] developed a RS model for almond orchards, accurately estimating actual ET and water stress using multispectral and thermal imagery. [PERSON] et al. [78] employed high-resolution satellite data and the METRIC model for precise almond tree crop ET estimation. [PERSON] et al. [79] investigated methods for separating transpiration (T) and evaporation (E) in almond orchards using the ALEXI modeling framework. [PERSON] et al. [80] assessed Multi-Sensor Data Fusion-Evapotranspiration (MSDF-ET) for estimating ETa from Landsat 8 data, displaying reliable results compared to eddy covariance measurements. [PERSON] and [PERSON] [81] used the TSEB model to study land use effects on ET in a California almond orchard, emphasizing the importance of high-resolution thermal imagery for precise estimates. [PERSON] et al. [82] analyzed agricultural water use in the California Central Valley using Landsat data, providing insights for sustainable groundwater management. Regarding studies using the satellite platform, six studies related to irrigation monitoring were identified. In [PERSON] et al. [83], Landsat 8 data is employed to monitor paddock-scale irrigation. Strong relationships (\(R^{2}\) between 0.72 and 0.85) between NDVI/EVI and ground-based crop water measurements show the effectiveness of RS for irrigation monitoring. On the other hand, [PERSON] et al. [84] studied the impact of soil management (conventional and vegetation cover) and irrigation levels on almond orchards from 2018 to 2020. They found that combining vegetation cover with optimal irrigation improves orchard performance, leading to increased biomass and yield. [PERSON] et al.