How the choice of model calibration procedure affects projections of lake surface water temperatures for future climatic conditions

Almost all hydrological models require calibration. The same model but with different parameters may lead to diverse simulations of the hydrological phenomena. Hence, the choice of a calibration method may affect the model performance. The present paper is the first study analyzing how the choice of air2water model calibration procedure may influence projections of surface water temperature in lowland lakes under future climatic conditions. To address this issue, projections from 14 atmospheric circulation models, data from 22 lowland Polish lakes located in a temperate climate zone, and 12 different optimization algorithms are employed. The studied lake areas range from 1.5 km² to 115 km², and their maximum depths range from 2.5 m to 70 m. Depending on which calibration algorithm is applied, the differences in mean monthly surface water temperatures projected for future climatic conditions may exceed 1.5 °C for a small deep lake. On the contrary, the differences observed for shallow and relatively large lakes, due to the optimization procedure used, were lower than 0.6 °C each month. The largest differences in projected lake water temperatures were observed for the winter and summer months, which are especially critical for aquatic biota. Among the optimization algorithms resulting in the largest differences were those that fit historical data well, as well as those that do not reproduce historical data appropriately. Therefore, strong performance for historical data does not guarantee reliable projections for future conditions. We have shown that projected lake water temperatures largely depend on the calibration method used for a particular model.