Land subsidence is probably one of the most evident environmental effects of groundwater pumping. Globally, freshwater demand is the leading cause of this phenomenon. Land subsidence induced by aquifer system drainage can reach total values of up to 14.5 m. The spatial extension of this phenomenon is usually extensive and is often difficult to define clearly. Aquifer compaction contributes to many socio-economic effects and high infrastructure-related damage costs. Currently, many methods are used to analyze aquifer compaction. These include the fundamental relationship between groundwater head and groundwater flow direction, water pressure and aquifer matrix compressibility. Such solutions enable satisfactory modelling results. However, further research is needed to allow more efficient modelling of aquifer compaction. Recently, satellite radar interferometry (InSAR) has contributed to significant progress in monitoring and determining the spatio-temporal land subsidence distributions worldwide. Therefore, implementation of this approach can pave the way to the development of more efficient aquifer compaction models. This paper presents (1) a comprehensive review of models used to predict land surface displacements caused by aquifer drainage, as well as (2) recent advances, and (3) a summary of InSAR implementation in recent years to support the aquifer compaction modelling process.
The environmental impact assessment of underground mining usually includes the direct effects of exploitation. These are damage to rock mass and land subsidence. Continuous dewatering of the aquifer system is, however, necessary to carry out underground mining operations. Consequently, the drainage of the aquifer system is observed at a regional scale. The spatial extent of the phenomenon is typically much wider than the direct impact of the exploitation. The research presented was, therefore, aimed at evaluating both the direct and the indirect effects of underground mining. Firstly, the spatial extent of land subsidence was determined based on the Knothe theory. Secondly, underground mining-induced drainage of the aquifers was modeled. The 3D finite-difference hydrogeological model was constructed based on the conventional groundwater flow theory. The values of model hydrogeological parameters were determined based on literature and empirical data. These data were also used for model calibration. Finally, the results of the calculations were compared successfully with the field data. The research results presented indicate that underground mining’s indirect effects cover a much larger area than direct effects. Thus, underground mining requires a broader environmental assessment. Our results can, therefore, pave the way for more efficient management of groundwater considering underground mining.
Earthquake occurrence is usually unpredictable apart from sites in the vicinity of volcanoes. It is not easy to measure displacements caused by seismic phenomena using classical geodetic methods, which are based on point survey. Therefore, the surveying of ground movements caused by seismic events should be carried out continuously. Nowadays, remote sensing data and InSAR are often applied to monitor ground displacements in areas affected by seismicity. The effects of severe nearby mining-induced earthquakes have been discussed in the paper. The earthquakes occurred in 2017 and had a magnitude of 4.7 and 4.8. The distance between the epicenters of the mining-induced earthquakes was around 1.6 km. The aim of the investigation has been to analyze the spatio-temporal distribution of ground movements caused by the two tremors using the InSAR technique. Superposition of surface displacement has been studied in time and space. The main scientific aim has been to prove that in the areas where high-energy tremors occur, ground movements overlap. Due to proximity between the epicenters, the mining-induced earthquakes caused the formation of a large subsidence trough with the dimension of approximately 1.2 km × 4.2 km and total subsidence of ca. 116 mm. Two-time phases of subsidence were determined with temporal overlapping. The subsidence analysis has enhanced the cognition of the impact of mining-induced seismicity on the kinematics of surface changes. Moreover, the present work supports the thesis that InSAR is a valuable and adequately accurate technique to monitor ground displacements caused by mining induced earthquakes.
The presented research aimed to evaluate the spatio-temporal distribution of ground movements caused by groundwater head changes induced by mining. The research was carried out in the area of one of the copper ore and anhydrite mines in Poland. To determine ground movements, classical surveying results and the persistent scatter Satellite Radar Interferometry (PSInSAR) method were applied. The mining operation triggered significant subsidence, reaching 1.4 m in the years 1944–2015. However, subsidence caused by groundwater pumping was about 0.3 m. After mine closure, an ongoing groundwater rebound was observed. Hence, land uplift occurred, reaching no more than 29 mm/y. The main part of the investigation concerned developing a novel method for uplift prediction. Therefore, an attempt was made to comparatively analyze the dynamics of ground movements correlated with the mine life and hydrogeological condition. These analyses allowed the time factor for the modeling of land uplift to be determined. The investigation also revealed that in the next six years, the uplift will reach up to 12 mm/y. The developed methodology could be applied in any post-mining area where groundwater-rebound-related uplift is observed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.