A Comparison of Model Calculations of Ice Thickness with the Observations on Small Water Bodies in Katowice Upland (Southern Poland)

Small bodies of water in densely populated areas have not yet been thoroughly studied in terms of their ice cover. Filling the existing research gap related to ice cover occurrence is therefore important for identifying natural processes (e.g., response to climate warming and water oxygenation in winter), and also has socio-economic significance (e.g., reducing the risk of loss of health and life for potential ice cover users). This paper addresses the issue of determining the utility of two simple empirical models based on the accumulated freezing degree-days (AFDD) formula for predicting maximum ice thickness in water bodies. The study covered 11 small anthropogenic water bodies located in the Katowice Upland and consisted of comparing the values obtained from modelling with actual ice thicknesses observed during three winter seasons (2009/2010, 2010/2011, and 2011/2012). The best fit was obtained between the values observed and those calculated using Stefan's formula with an empirical coefficient of 0.014. A poorer fit was obtained for Zubov's formula (with the exception of the 2011/2012 season), which is primarily due to the fact that this model does not account for the thickness of the snow accumulated on the ice cover. Bengst'cise forecasting of the state of the ice cover and the provision of the relevant information to interested users will increase the safety of using such water bodies in climate warming conditions, reducing the number of accidents.

Automated summary

The ice cover in small bodies of water in densely populated areas has not been thoroughly studied. Filling this research gap is important for understanding natural processes and has socio-economic significance. This study compares two empirical models based on freezing degree-days formula for predicting maximum ice thickness in water bodies. The results show that the Stefan's formula with an empirical coefficient of 0.014 provides the best fit.