Probabilistic Analysis as a Method for Ground Freezing Depth Estimation

Accurate frost depth prediction is an important aspect in different engineering designs such as for pavements, buildings, bridge foundations, and utility lines. This paper presents a probabilistic method of assessment of the depth of soil freezing. Annual (winter) maxima of the position of the zero centigrade temperature measured in the soil were approximated by Gumbel probability distribution. Its parameters were estimated using maximum likelihood method. The results received on the basis of data from 36 meteorological stations in Poland and 50 years of observations, as characteristic values with 50-year return period, reflect the influence of the climatic conditions on the freezing depth. On the other hand, the soil structure and its conditions also play an important role in freezing. Nowadays they may be taken into account using correction coefficients. It is concluded that this method is more precise than a method using the air freezing index because through the use of direct measurements it takes into account additional factors affecting the actual depth of freezing. The obtained results are not the same as those given in the older Polish Standard which was based on the simplified and limited data. The results confirm the impact of climate change on ground freezing depth.