Four precise leveling campaigns has been carried out in Poland, and for several years there is a functioning system of permanent GNSS stations determining the height of network points. On the basis of these data, several variants of vertical crustal movements models have been developed (Wyrzykowski, 1987; Kowalczyk, 2005; Kontny and Bogusz, 2012). In order to develop a kinematic model of vertical crustal movements, one of the possibilities is an adjustment of the network formed simultaneously with the leveling data and GNSS stations data. The main problem is a need to identify fiducial points between the datasets. This problem can be solved by creation of coherent database containing attributes of both types of data and automatization of the joint point identification process. The article shows the results of such identification process, depending on the amount of data, on the example of the area of Poland. and Bednarczyk Michal, Kowalczyk Kamil, Kowalczyk Anna.
Surface deformation due to underground exploitation affects the safety of overlying structures. Forecasting can predict risks to surface structures and facilitates actions designed to improve their resilience and reduce the potential impact of mining activities. However, forecasting accuracy is limited. Therefore, in practice, model parameters are determined within a certain margin to ensure that critical values of deformation indicators for surface objects are not exceeded. For economic reasons, it is important to minimize these margins while also ensuring that safety is maintained. One important factor influencing forecasting accuracy is the uncertainty in deformation model parameters used for calculations. Therefore, it is critical to adopt an appropriate methodology for determining and addressing the uncertainties in deformation model parameters used in forecasting. This study presents methods for estimating the Knothe's model parameters needed to forecast surface deformation caused by underground mining and defining the uncertainties in those forecasts. Depending on the parameter uncertainties, one of two methods for propagation is proposed: the Monte Carlo method or the law of propagation of uncertainty. Using this approach, it is possible to account for uncertainty and reduce forecast margins. A case study of hard coal mining in the Upper Silesian Coal Basin region of Poland is presented., Wojciech Gruszczyński, Zygmunt Niedojadło and Dawid Mrocheń., and Obsahuje bibliografii