## 1 Introduction
This growth is particularly notable in the La Mancha region, where high evaporative demand and scarce summer rainfall coincide with the peak water requirements in many crops, including nut tree orchards and vineyards. For example, [PERSON] et al. [29] estimated the irrigation water requirements in our study area for one of the largest irrigation water user associations in La Mancha, using remote sensing techniques. These authors reported that, from May to August, the irrigation water requirements reached the higher water demands across four consecutive years [30]. In this sense, the water use efficiency (WUE) index is a crucial sustainability indicator that measures how effectively almond trees convert water into biomass, particularly in arid and semi-arid regions where water scarcity is a major constraint on crop development and yield [31; 32; 33]. WUE is defined as the amount of carbon assimilated as biomass or marketable yield per unit of water consumed by the crop or crop ET [34]. Remote sensing ET and yield estimation models have improved the accuracy at the regional scale, and the incorporation of crop types and irrigation allocations into high-spatial-resolution crop-specific WUE modeling is the recommended method of WUE estimation [35] in almond crops. For example, [PERSON] et al. [36] recently measured the ratio between total dry mass and water used in four different almond cultivars that were one year old. At the leaf level, several studies have addressed instantaneous and/or intrinsic WUE in almond orchards [37; 38]. Other studies have determined the water use, ET and crop coefficients in young almond orchards using the EC system, by gas-exchange methods [39] or by soil water balance [40] under deficit conditions to optimize irrigation management based on tree development and local conditions [41; 42; 43]. However, to the best of our knowledge, ecosystem WUE (eWUE), calculated as the ratio between GPP and evapotranspiration (ET) [44; 45], which can better represent the crop behavior at a larger spatial scale, has not been previously reported for almond trees [44; 45]. In the context of climate change, parametrizing eWUE is crucial for understanding and addressing the evolving dynamics of water management, emphasizing its pivotal role in sustainable adaptation strategies. Modeling eWUE presents a significant challenge due to the complex interplay of various environmental factors and dynamic system interactions [46]. However, in this work, eWUE is parametrized based on vegetation indices and easily accessible meteorological data, which play a key role in optimizing water use in agriculture. This approach helps preserve water resources, adapt to changing climate conditions, and achieve both economic and environmental sustainability. Various authors have also correlated these variables, obtaining similar results in other crops, such as olives [47]. This approach may be a valuable tool for farmers, researchers, policymakers, and water resource managers striving to address the challenges associated with efficient water use in agriculture. In the present study, Eddy Covariance (EC) flux towers were used to determine NEE, ET and GPP [48]. This advanced technology is able to continuously monitor gas, heat, and water vapor fluxes between vegetation and the atmosphere. Not only does this methodology provide detailed insights into ecosystem and agriculture water use efficiency, but it also significantly contributes to carbon cycle assessments and the development of effective climate change mitigation strategies. However, despite their accuracy, EC data have limitations in spatial representativeness because they only capture detailed information about ecosystem dynamics at their specific location and do not provide a broader view of ecosystem trends [49]. Moreover, complex terrain and dense vegetation can significantly affect the measurements from the EC tower, potentially leading to uncertainties [50; 51].