Extending Class A pan evaporation for a shallow lake to simulate the impact of littoral sediment and submerged macrophytes: a case study for Keszthely Bay (Lake Balaton, Hungary)

摘要

Class A pan evaporation rate,Epwith sediment cover (S) and submerged aquatic macrophytes (Ps) was analysed in a temperate freshwater shallow lake at Keszthely (Hungary), over three growing seasons between 2014 and 2016. The aim was to identify the importance of this water body’s natural components (SandPs) onEp. MeasuredEptogether with referenceEof Shuttleworth (E0) and the FAO-56 equationETwere also derived. Pan coefficient,Kafor filled in pans withSandPswere computed as the ratio ofEpof the planted pan (Ps/S) andEp.Kavalues determined on-site were tested in the estimation ofEfor an open water body, namely Keszthely Bay of Lake Balaton. Overall seasonal mean evaporation rate was lower forEp(3.2?±?1.05?mm?day?1) than the seasonal daily averageEpofS(3.7?±?1.16?mm?day?1) and theEpofPs(4.0?±?1.28?mm?day?1). Interannual variation ofEpwas controlled by variations in seasonal air temperature,Ta. Data of the wet 2014 season showed a significant suppression ofEp, and this was related to humid and cooler weather conditions causing late emergence and early senescence of the submerged macrophytes (Potamogeton perfoliatusL.,Myriophyllum spicatumL. andNajas marinaL.) at Keszthely Bay. Overall seasonal meanKawas greater than 1.0?as determined for the three-season time period in pans withSandPs(Kas: 1.14?±?0.04;Kap: 1.20?±?0.05). Except for a previous study from our group (, J Hydrol 542: 615–626) over a two-season period, no such ratio or coefficients have been published, until now. The dominant component of the energy balance was latent heat flux, which accounted for more than 60% of net radiation in Keszthely Bay, depending on Class A pan filling (SandPs). Diurnal variation in heat storage of the pan also changed due to the occurrence of sediment cover and macrophytes inside the evaporimeters. The most important daily meteorological variables were used to develop theEpmodel and to validateSandPs. Our results show that linear models, even with more input variables, performed better than tree-based models with respect to mean absolute errors (MAE), root mean square errors (RMSE) and determination coefficient (R2) in predicting dailyEpofSandPs. The use of pan coefficientsKasandKapincreased seasonalEof Keszthely Bay by 4.2, 14.4 and 17.1% during the 2014–2016 seasons, respectively. Total seasonal increments for Keszthely Bay (surface area is about 39 km2) accounted for 0.97, 4.31 and 3.91 million m3throughout 2014–2016, respectively. In the warmer seasons, an increasing trend in the growth of Keszthely Bay’sEwas detected. These results indicate that Class A panEprates need to be modified to take into account sediment cover and submerged macrophytes to derive open waterE. This approximation may lend additional credit to the estimation ofEin lakes. Given that appropriate estimation ofEcan effectively impact the management of an ecologically functional lake’s water, maintaining the proper water level and quality can contribute to the sustainability of lakes in the long run.