Eva Jirankova

The reliable prediction of mining-induced subsidence in deep multi-seam environments is fundamentally hindered by a kinematic contradiction: classical Influence Function Methods (IFMs) impose a Linear Shift-Invariant (LSI) Gaussian kernel that structurally cannot reproduce sharp shear boundaries, pillar relief, or trap-door failures, regardless of parameter tuning. This paper introduces the Spatio-Temporal Interaction and Geometrically Adaptive Influence Function Method (STIGA), a macroscopic phenomenological model of rock mass degradation that redefines the subsidence field as a Generalized Superposition Integral over a Linear Shift-Variant (LSV) medium. The influence kernel evolves endogenously from a diffusive Gaussian profile ($n=2$) to a shear-controlled Super-Gaussian piston ($n>2$) via the Hydraulic Radius ($R_h$), resolving the ``Soft Edge'' artifact without recourse to discontinuum mechanics. Multi-seam interactions are quantified through a Cumulative Extraction Density (CED) that couples surface deformation to the cumulative damage history of the rock mass. Although originally motivated by the need to supply continuous surface priors for numerical model calibration, where sparse, discontinuous monitoring points render the inverse problem under-determined, the calibrated framework proves to be a self-sufficient predictive engine. By anchoring constitutive variables to macroscopic geomechanical clusters, STIGA decouples geometric resolution from parameter dimensionality and generates physically valid continuous surfaces directly from the 3D mine schedule. A hybrid inverse strategy (CMA-ES, Huber Loss) is validated against a 20-year dataset from the \v{C}SM Mine, demonstrating that the framework reconstructs unrecorded subsidence, captures abrupt multi-seam shear ruptures, and outperforms classical literature-constrained models by an order of magnitude in volumetric fidelity.

The termination of mining activities often results in post-mining problems and risks. One of these issues is the flooding of mines. Long-term mining in the Ostrava and Petrvald sub-basins in the Upper Silesian Coal Basin finished in 1994. Tens of coal seams were mined here, and the depth of mining reached more than 1000 m below the surface. Flooding of the Ostrava sub-basin started in 1994. The Ostrava and Petrvald sub-basins were flooded from one half only to prevent water from flooding into the Karvina sub-basin, where mining continued. The continual pumping of water has been carried out ever since. Only low-energy seismic events (up to 103 J) were recorded during the periods of flooding and water pumping. Only one high-energy seismic event was recorded here (108 J, magnitude of 3.5, 12 December 2017). This study presents the natural and mining conditions regarding the process of mine flooding; and the induced seismicity registered during the flooding of mines and the preservation of water at the stated level. Analysis of the flooding of mines in connection to the registered seismicity is presented. Probable reasons for the low seismic activity during the flooding of mines are also discussed.

The Sentinel-1 satellite system continuously observes European countries at a relatively high revisit frequency of six days per orbital track. Given the Sentinel-1 configuration, most areas in Czechia are observed every 1–2 days by different tracks in a moderate resolution. This is attractive for various types of analyses by various research groups. The starting point for interferometric (InSAR) processing is an original data provided in a Single Look Complex (SLC) level. This work represents advantages of storing data augmented to a specifically corrected level of data, SLC-C. The presented database contains Czech nationwide Sentinel-1 data stored in burst units that have been pre-processed to the state of a consistent well-coregistered dataset of SLC-C. These are resampled SLC data with their phase values reduced by a topographic phase signature, ready for fast interferometric analyses (an interferogram is generated by a complex conjugate between two stored SLC-C files). The data can be used directly into multitemporal interferometry techniques, e.g., Persistent Scatterers (PS) or Small Baseline (SB) techniques applied here. A further development of the nationwide system utilising SLC-C data would lead into a dynamic state where every new pre-processed burst triggers a processing update to detect unexpected changes from InSAR time series and therefore provides a signal for early warning against a potential dangerous displacement, e.g., a landslide, instability of an engineering structure or a formation of a sinkhole. An update of the processing chain would also allow use of cross-polarised Sentinel-1 data, needed for polarimetric analyses. The current system is running at a national supercomputing centre IT4Innovations in interconnection to the Czech Copernicus Collaborative Ground Segment (CESNET), providing fast on-demand InSAR results over Czech territories. A full nationwide PS processing using data over Czechia was performed in 2017, discovering several areas of land deformation. Its downsampled version and basic findings are demonstrated within the article.

Sentinel-1 satellite system continuously observes European countries in a relatively high revisit frequency of 6 days per orbital track. Given the Sentinel-1 configuration, most areas in Czechia are observed every 1–2 days by different tracks in a moderate resolution. This is attractive for various types of analyses by various research groups. The starting point for processing is an original data provided by ESA, for interferometry (InSAR) this level is a Single Look Complex (SLC) data. This work represents advantages of storing data augmented to a specifically corrected level of data, SLC-C. The presented database contains Czech nation-wide Sentinel-1 data stored in burst units that have been preprocessed to the state of a consistent well-coregistered dataset of SLC-C. These are resampled SLC data with their phase values reduced by a topographic phase signature, ready for fast interferometric analyses (an interferogram is generated by a complex conjugate between two stored SLC-C files). The data can be used directly into multitemporal interferometry techniques, e.g. Persistent Scatterers (PS) or Small Baseline (SB) techniques applied here. A further development of the nation-wide system utilising SLC-C data would lead into a dynamic state where every new pre-processed burst triggers a processing update to detect unexpected changes from InSAR time series and therefore provide a signal for early warning against a potential dangerous displacement, e.g. a landslide, instability of an engineering structure or a formation of a sinkhole. An update of the processing chain would also allow use of cross-polarised Sentinel-1 data, needed for polarimetric analyses. The current system is running at a national supercomputing centre IT4Innovations in interconnection to the Czech Copernicus Collaborative Ground Segment (CESNET), providing fast on-demand InSAR results over Czech territories. A full nation-wide PS processing using data over Czechia has been performed in 2017, discovering several areas of land deformation. Its downsampled version and basic findings are demonstrated within the article.