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

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

Classification of Water Reservoirs in Terms of Ice Phenomena Using Advanced Statistical Methods—The Case of the Silesian Upland (Southern Poland)

Ice phenomena occurring in water bodies are an important indicator of natural changes (e.g., climate change) and the possibilities for economic use of water bodies (e.g., using the ice cover); hence, there is a need to adopt new advanced statistical methods for the purpose of their analysis and assessment. Material for this study was collected for three winter seasons in 39 water bodies in the Silesian Upland (southern Poland). Nine variables were used in the analysis, of which three pertained to the features of the water bodies studied (surface area, mean depth, the amount of water retained), and six pertained patterns to of ice phenomena (average near-surface water temperature during ice phenomena, average and maximum ice thickness, the number of days with ice phenomena, the number of days with ice cover, and average thickness of the snow accumulated on ice). The centroid class principal component analysis (CCPCA) method was found to be the most precise of the five methods used in the study for classifying water bodies in terms of their ice regimes. It enabled the most accurate division of the group of water bodies covered by the study in terms of their ice regimes in conjunction with their morphometric features and hydrological types. The presented method of classifying water bodies using advanced statistical methods is an original proposal, which was used for the first time in limnological research and in the analysis of ice phenomena

Determinants of Spatial Variability of Ice Thickness in Lakes in High Mountains of the Temperate Zone—The Case of the Tatra Mountains

Vertical and horizontal variation in the ice cover of mountain lakes in the temperate climate zone has not been thoroughly studied. The study concerned ice phenomena in four lakes located in the Tatra National Park in the Tatra Mountains (the Czarny Staw Gąsienicowy, Czarny Staw pod Rysami, Morskie Oko, and Smreczyński Staw). The research, which was conducted in the 2018/2019 winter season, included an analysis of variability in atmospheric conditions, an analysis of presence of ice phenomena on satellite images, field work (measurements of ice layer and of snow and slush layer thickness were conducted at a total of 151 sites), and statistical analyses. It was determined that negative air temperature was just one factor among those that determined the maximum thickness of the ice forming on lakes in high mountains. It was found that in addition to ambient thermal conditions, a major factor affecting the magnitude of variation in lake ice thickness was the thickness of the snow overlying the ice and its spatial variability. Thicker ice cover tended to form in areas where a thick layer of snow was deposited. The decisive factor that contributed to a significant variation in ice thickness between lakes was the uneven accretion of snow ice from above. The maximum ice thickness values modeled using Stefan’s formula were significantly underestimated (accounting for 38–61% of the ice thickness measured) relative to the highest ice thickness values found empirically at the end of the winter season. Study results fill a gap in our knowledge and methodology related to vertical and horizontal variation in the ice cover of mountain lakes; they also have significant applications, indicating the risk of winter use of water bodies with different ice cover structure, thickness, and extent