## 4 Discussion
### Crop Coefficients (Kc) Derived from NDVI: Relevance of Kc Variability  
The seasonal variability of Kc derived from the NDVI provided a more accurate representation of the water requirements for the avocado orchard. The Kc values, derived from the NDVI, followed clear seasonal trends that mirrored the vegetative phases of the avocado trees. Peak Kc values coincided with the maximum canopy greenness observed in the middle of the growing season, indicating a period of high water demand. This is consistent with the findings from the literature that crop water requirements are highest during peak vegetative growth, which aligns with the observed increase in Kc. For instance, in a prior study [64], the authors aimed to enhance evapotranspiration estimates by integrating NDVI-derived Kc for precise water management in croplands; they noted that NDVI-derived Kc was able to effectively reflect the crop water demand, aligning with water stress indicators by capturing vegetation health and growth dynamics and becoming an aid in precision irrigation and stress mitigation. The advantage of using the satellite-derived NDVI to calculate Kc is the ability to derive dynamic, spatially explicit Kc values responsive to seasonal changes in vegetation health and water availability [65; 66]. These values offer a more detailed and accurate estimate of water requirements than the static tabular values typically used in traditional irrigation scheduling. In contrast to standard Kc values, which are fixed for specific crop types and growth stages, the NDVI-based Kc values reflect the actual condition of the vegetation, adjusting in real time to changes in canopy development, soil moisture, and weather conditions. Moreover, the Kc values derived from the NDVI, SAVI, and NDWI were validated by comparing them with published values for avocado orchards in similar agroecological conditions. The estimated Kc values were also analyzed alongside soil moisture data to ensure consistency with field observations. The agreement between the vegetation-index-derived Kc values and seasonal water stress patterns observed in soil moisture measurements supports the applicability of these empirical relationships for irrigation management. Despite these advantages, the use of VIs and WIs for estimating Kc presents certain limitations that must be considered, given that the accuracy of Kc estimations derived from remote sensing data can be influenced by several environmental and agronomic factors such as the following: (i) Variety differences: Different avocado cultivars exhibit variations in their canopy structure, leaf area index (LAI), and stomatal conductance, which may affect the spectral response captured by the NDVI, SAVI, and NDWI. As a result, the empirical equations used to derive Kc from these indices may require calibration to account for varietal differences. (ii) Soil type influence: Soil texture and composition impact water retention, infiltration rates, and root-zone moisture availability, affecting how vegetation indices reflect the actual water status. For instance, in areas with heterogeneous soil properties, additional calibration or integration with soil moisture measurements may be required. (iii) Climate variability: Meteorological conditions such as the temperature, humidity, and wind speed influence the water-use efficiency and evapotranspiration rates; therefore, the spectral response of VIs and WIs may vary under extreme climatic conditions (e.g., prolonged droughts or excessive rainfall), potentially affecting Kc estimations. Implications for Irrigation Scheduling  
Seasonally varying Kc values derived from the NDVI can significantly enhance irrigation efficiency, especially under water-limited conditions. Using dynamic Kc values, irrigation schedules can be more accurately tailored to the crop's actual water needs, reducing water waste during less demanding periods and ensuring adequate irrigation during high-demand phases, such as the mid-growing season.