In this study, we present the efficiency of remediation scenario to attenuate the impact of acid mine drainage (AMD) contamination in the Kettara abandoned mine site. The study focuses on the AMD groundwater contamination of the Sarhlef shists aquifer. To predict the evolution of AMD groundwater contamination in the Kettara mine site under remediation scenario, a model of groundwater flow and AMD transport was performed.Piezometric heads were measured at the dry and wet periods from eleven wells located downstream of mine wastes. To elaborate a conceptual groundwater flow model, we faced with to the heterogeneity and anisotropy of fractured Sarhlef shists aquifer. Consequently, the study focused on the use of various approaches: 1. The inverse modeling by the CMA-ES algorithm is adopted as an alternative approach to determine hydraulic parameters indirectly, and 2. the model is treated as an equivalent porous media (EPM). The groundwater flow model was carried out in steady-state and transient conditions in the dry and wet periods using the PMWIN interface. The obtained results are satisfactory and show an excellent correlation between measured and computed heads. Contaminant transport model is used to solve the advection–dispersion equation and to generate the AMD concentration by MT3D via the PMWIN interface. A sensitivity analysis of the dispersivity coefficient is carried out. The AMD transport simulation was computed during periods of 1, 5 and 10 years, and the performed model indicates that the simulated concentrations under remediation scenario are reduced 1000 times comparing to the current concentrations. The study revealed a necessary approach in addressing an environmental issue for the AMD contamination. The results of the study will be a start-up for further research work in the study area and implementing it for the prevention of AMD propagation plume.
Gravity-based imaging of the subsurface has increased worldwide recently. Improvements in the processing and analysis of gravity data have allowed us to locate the basement surface, map geologic basins, and define structural patterns. In this study, gravity data were analyzed to study the Bahira basin’s underlying geology. The Bahira basin is very important economically. The Ganntour plateau is distinctive due to the importance of the phosphate mining resources. Using gravity data, we mapped the subsurface and determined the underlying structural patterns that affect the study area. In this study, we used several techniques to edge detection including Total horizontal derivative (THDR), first vertical derivative (FVD), tilt derivative (TDR), and its horizontal derivative (THDR_TDR) methods. Accordingly, the geological history of the Bahira basin suggests that the main lineaments/faults trends are NE-SW, NW-SE, ENE-WSW, and WNW-ESE. The 3D Euler deconvolution showed the depth and location of lineaments/faults, and matched edge detection results. The eastern Bahira basin’s sedimentary layer is 2–8 km deeper according to the Euler technique. Two-dimensional forward modeling along three profiles in the Bahira basin revealed a horst-graben basement structure. The outcomes of this study improved the subsurface topographical variations of the Bahira Basin. The information collected so far can help future studies in the area.
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