Abstract:

Google Earth Engine (GEE) is a cloud-based platform widely used in geospatial analysis, which allows users to work with large volumes of climatic and environmental data through programming and integrated visualization tools. In the context of the Crop Science (Fitotecnia) course, one of the recurring challenges in teaching is understanding reference evapotranspiration (ETo) and, more generally, the energy balance associated with water movement in the soil–plant–atmosphere system. These processes are essential for irrigation planning and crop growth, but their non-directly observable nature and complex physico-mathematical formulation hinder students’ understanding.

The FAO-56 Penman–Monteith equation integrates multiple meteorological variables, such as mean air temperature (T), saturation vapour pressure (es), actual vapour pressure (ea), vapour pressure deficit (es – ea), net radiation (Rn) and wind speed at 2 m (u2), whose relative contribution to the final result is not evident to students without systematic data analysis. The educational objectives of the activity are to improve students’ ability to interpret the role of each climatic variable, understand their contribution to the ETo formulation, and develop data-driven reasoning in irrigation-related decision-making.

To address this issue, a teaching activity is presented that integrates GEE and global meteorological data from ERA5-Land for the dynamic calculation of ETo. Students can select different locations across the globe and analyse the daily variation of ETo as a function of geographical and seasonal context, which makes it possible to relate evaporative demand to contrasting climatic conditions. In addition, it will be possible to generate ETo maps at a regional scale (e.g., for the whole of Spain) that allow the visualisation of spatial gradients of evaporative demand under different climatic conditions. This approach provides added value compared with traditional explanations, as students work directly with real meteorological datasets displayed in an interactive cloud-based platform.

The activity includes the graphical representation of the climatological variables involved in the equation and the generation of correlation analyses between these variables and the resulting ETo. This approach facilitates the interpretation of functional relationships between the components of the energy balance and enables the gradual introduction of basic statistical concepts applied to agronomic data. The use of GEE in this context provides a working framework based on real data, reproducible programming, and integrated visualization, which contributes to improving the understanding of ETo, the soil–plant–atmosphere system, and its relevance for decision-making in Agronomy. Initial feedback from students suggests increased engagement, enhanced understanding of climatic drivers of ETo, and greater confidence in using geospatial data with digital tools.

Keywords:

Google Earth Engine (GEE), Reference Evapotranspiration (ETo), Crop Science, Digital Skills.