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.

Highlights

  • Open water evaporation is one of the paramount elements of the hydrological cycle (Brutsaert, 1982)

  • FAO-56 Penman-Monteith equation (FAO56-PM), multiple stepwise regression (MLR) and Kohonen self-organizing map (KSOM) 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 10 macrophytes (Myriophyllum sipctatum., Potamogeton perfoliatus, and Najas marina), in an six-season experiment

  • We developed Ep models based on three different approaches (FAO56-PM, MLR and Kohonen Self Organizing Maps (K-SOM)) with daily meteorological variables, and tested the performance of the models by four commonly used statistical indicators (MAE [Ideal = 0, (0,+∞)], root mean square error (RMSE) [Ideal = 0, (0,+∞) ], Nash-Sutcliffe efficiency (NSE) [Ideal = 1, (−∞,1)], scatter index (SI) [Ideal = 0, (0,+∞)])

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Summary

Introduction

Open water evaporation is one of the paramount elements of the hydrological cycle (Brutsaert, 1982). It is extremely important to determine evaporation as accurately as possible (Fournier et al, 2021), for which both direct and indirect methods 25 are available. The evaporation pans (primarily the class A pan proposed by the World Meteorological Organization, WMO) are used extensively throughout the world to measure open water evaporation and to estimate reference evapotranspiration (Rahimikhoob, 2009). 30 To indirectly determine evaporation, several methods can be used: empirical equations are applied that estimate evaporation based on meteorological variables (air temperature, Ta, relative humidity, RH, global radiation, Rs), or transfer and water budget methods (Burman, 1976). The most widely used empirical formula is a FAO-56 Penman–Monteith equation (FAO56PM) (Allen et al, 1998), which is the standard method for computation of daily reference evapotranspiration. Measuring meteorological variables requires sophisticated instruments, which can often be challenging

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