“…For this reason, models to estimate ETo have been developed during the last decades, using machine learning techniques such as Artificial Neural Networks (ANN) (Zanneti et al, 2008;Alves et al, 2017;Fonseca et al, 2018;Laqui et al, 2019;Meneses et al, 2020) Autoregressive Integrated Moving Average Model (ARIMA) (Jordan et al, 2008;Gautam and Sinha, Mossad and Alazba, 2016;Bouznad et al, 2020), and Multiple Linear Regression (MLR) (Yirga, 2019). In Colombia, the spatial distribution of climatological stations is uneven due to several factors, such as complex topography (e.g., the Andean Mountain range), areas affected by the armed conflict, and low investment in technological resources, among others (Urrea et al, 2019;Canchala et al, 2022). In southwestern Colombia (Nariño), 76 % of the rainfall stations are in the Andean region, with a density of one station every 470 km2, covering 40 % of the total area of Nariño.…”