SIMO v1.0: Simplified model of the vertical temperature profile in a small warm monomictic lake

Abstract

Abstract. A simple 1-D energy budget model (SIMO) for the prediction of the vertical temperature profiles in small, monomictic lakes forced by a reduced number of input meteorological variables is proposed. The model estimates the net heat flux and thermal diffusion using only routinely measured hourly mean meteorological variables (namely, the air temperature, relative humidity, atmospheric pressure, wind speed, and precipitation), hourly mean ultraviolet B radiation (UVB), and climatological monthly mean cloudiness 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 (Lake 1 and Lake 12). Temperatures were measured at 15 and 16 depths ranging from 0.2 to 27 in Lake 1 (maximum depth of 37.4\u2009m) and 0.2 to 43\u2009m in Lake 12 (maximum depth of 46\u2009m). A sensitivity analysis of the simulation length was performed for simulation lengths from 1 to 30 days. 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. A yearlong simulation initiated with an approximately constant vertical profile of the lake temperature (≈\u20094\u2009°C) was able to reproduce the onset of stratification and convective overturn. However, the thermocline depth was underestimated while the epilimnion temperatures were overestimated. Nevertheless, the values of the model performance measures obtained for a yearlong simulation were comparable with those reported for other more complex models. Thus, the presented model can be used for the assessment of the onset and duration of lake stratification periods when water temperature data are unavailable, which can be useful for various lake studies performed in other scientific fields, such as biology, geochemistry, and sedimentology.