SIMPLE ONE-DIMENSIONAL LAKE TEMPERATURE PREDICTION MODEL (SIMO V1.0)

Water temperature directly influences a range of lake properties such as the solubility of gases and minerals or the rate of chemical reactions. The vertical water temperature profile determines the water column stability and has a significant role in the vertical transport of gases and nutrients, consequently affecting the biological activity and diversity in the lake. The thermodynamic behavior of lakes is affected by many processes including shortwave and longwave radiation, attenuation of light, sensitive and latent heat flux, sediment heat flux, phase change of water, convective and turbulent mixing, and wind sheltering. However, the main driver are the meteorological conditions determining the heat flux at the lake surface. Here, a simple 1-D energy budget model (SIMO) for the prediction of the vertical temperature profiles in small, monomictic lakes is proposed. The goal was to develop a model that estimates the net heat flux and vertical thermal diffusion using only routinely measured hourly mean meteorological variables. Namely, the proposed model employs carefully chosen parameterizations to calculate surface heat flux components, such as longwave and shortwave radiation, using only the air temperature, relative humidity, atmospheric pressure, wind speed, precipitation and ultraviolet B radiation (UVB). The only additional data needed are the climatological yearly mean air temperature data. Except for the initial vertical temperature profile, the model does not use any lake-specific variables. The model performance was evaluated against lake temperatures measured continuously during an observational campaign in two lakes belonging to the Plitvice Lakes, Croatia (Prošće and Kozjak). Temperatures were measured at 15 and 16 depths ranging from 0.2 to 27 in Prošće (maximum depth of 37.4 m) and 0.2 to 43 m in Kozjak (maximum depth of 46 m). Common bivariate measures were used: mean bias error, mean absolute error, root mean square error and maximum absolute error, as well as index of agreement. Results from simulations of different lengths, ranging from 1 to 30 days, were used to evaluate the model performance sensitivity to the simulation length. The model performed reasonably well and it was able to satisfactorily reproduce the vertical temperature profile at the hourly scale, the deepening of the thermocline with time, and the annual variation in the vertical temperature profile. The ability of the model to predict the springtime onset of lake stratification and autumn convective overturn was also examined by running a yearlong simulation initiated with an approximately constant vertical profile of the lake temperature (~ 4°C). The model was able to reproduce the lake stratification. The upper limit of the metalimnion was well captured while it‟s thickness was overestimated. The epilimnion temperature was also somewhat overestimated. Nevertheless, the values of the model performance measures of the yearlong simulation were comparable with those reported for other more complex models. This shows that the presented model can be used for assessment of the onset and duration of lake stratification periods when no water temperature data are available, as well as for long term simulations for climate change impacts assessment.