Abstract. Evaporation is an important meteorological variable that has also a great impact on water management. In this study, FAO-56 Penman-Monteith equation (FAO56-PM), multiple stepwise regression (MLR) and Kohonen self-organizing map (K-SOM) techniques were used for the estimation of daily pan evaporation (Ep) in three treatments, where C was the standard class A pan with top water, S was A pan with sediment covered bottom, and SM was class A pan containing submerged macrophytes (Myriophyllum sipctatum., Potamogeton perfoliatus, and Najas marina), in an six-season experiment. The modelling approach included six measured meteorological variables; daily mean air temperatures (Ta), maximum and minimum air temperatures, global radiation (Rs), relative humidity (RH), and wind speed (u) in the 2015–2020 growing seasons (from June to September), at Keszthely, Hungary. Average Ep varied from 0.6 to 6.9 mm d−1 for C, 0.7 to 7.9 mm d−1 for S, whereas from 0.9 to 8.2 mm d−1 for SM during the growing seasons studied. Correlation analysis and K-SOM visual representation revealed that Ta and Rs had stronger positive correlation, while RH had a negative correlation with the Ep of C, S and SM. Performances of the different models were compared using statistical indices, which included the root mean square error (RMSE), mean absolute error (MAE), scatter index (SI) and Nash-Sutcliffe efficiency (NSE). The results showed that the MLR method provided close compliance with the observed pan evaporation values, but the K-SOM method gave better estimates than the other methods. Overall, K-SOM has high accuracy and huge potential for Ep estimation for water bodies where freshwater submerged macrophytes are present.