This publication provides guidance to water-sector decision makers and planners on how to deal with the quality dimension of groundwater resources management in the World Bank's client countries. There is growing evidence of increasing pollution threats to groundwater and some well-documented cases of irreversible damage to important aquifers. This guide has been produced in the belief that groundwater pollution hazard assessment must become an essential part of environmental best practice for water supply utilities. The guide is particularly relevant for the World Bank's Latin American and Caribbean Region, where many countries have initiated major changes to modernize their institutional and legal framework for water resources management, but may not yet have considered groundwater at the same level as surface water, because of lack of awareness and knowledge of groundwater issues and policy options.

The geochemical and isotopic composition of surface waters and groundwater in the Velenje Basin, Slovenia, was investigated seasonally to determine the relationship between major aquifers and surface waters, water–rock reactions, relative ages of groundwater, and biogeochemical processes. Groundwater in the Triassic aquifer is dominated by HCO₃–, Ca²⁺, Mg²⁺and δ¹³CDICindicating degradation of soil organic matter and dissolution of carbonate minerals, similar to surface waters. In addition, groundwater in the Triassic aquifer has δ¹⁸O and δD values that plot near surface waters on the local and global meteoric water lines, and detectable tritium, likely reflecting recent (<50 years) recharge. In contrast, groundwater in the Pliocene aquifers is enriched in Mg²⁺, Na⁺, Ca²⁺, K⁺, and Si, and has high alkalinity and δ¹³CDICvalues, with low SO₄²–and NO₃–concentrations. These waters have likely been influenced by sulfate reduction and microbial methanogenesis associated with coal seams and dissolution of feldspars and Mg-rich clay minerals. Pliocene aquifer waters are also depleted in¹⁸O and²H, and have³H concentrations near the detection limit, suggesting these waters are older, had a different recharge source, and have not mixed extensively with groundwater in the Triassic aquifer.

Water inrush from coal-seam floors greatly threatens mining safety in North China and is a complex process controlled by multiple factors. This study presents a mathematical assessment system for coal-floor water-inrush risk based on the variable-weight model (VWM) and unascertained measure theory (UMT). In contrast to the traditional constant-weight model (CWM), which assigns a fixed weight to each factor, the VWM varies with the factor-state value. The UMT employs the confidence principle, which is more effective in ordered partition problems than the maximum membership principle adopted in the former mathematical theory. The method is applied to the Datang Tashan Coal Mine in North China. First, eight main controlling factors are selected to construct the comprehensive evaluation index system. Subsequently, an incentive-penalty variable-weight model is built to calculate the variable weights of each factor. Then, the VWM-UMT model is established using the quantitative risk-grade divide of each factor according to the UMT. On this basis, the risk of coal-floor water inrush in Tashan Mine No. 8 is divided into five grades. For comparison, the CWM is also adopted for the risk assessment, and a differences distribution map is obtained between the two methods. Finally, the verification of water-inrush points indicates that the VWM-UMT model is powerful and more feasible and reasonable. The model has great potential and practical significance in future engineering applications.

A variable-volume, head-dependent mine water filling model (MIFIM) has been utilized to simulate the post-abandonment flooding of the Siersza coal mine in the Upper Silesian Coal Basin of southern Poland. It is demonstrated that desaturated pore space in the aquifer adjacent to the mine comprises a significant component of the resaturable mine-related void. The model results are very sensitive to the value of this poorly constrained parameter. Nevertheless, the model successfully predicted the first appearance of mine water in an observation well and its subsequent rise. Despite this apparent success, it is concluded that such modeling approaches generally lack predictive power for mines in permeable, porous host rocks. As real monitoring data accumulate, however, such models can be calibrated and their utility increased.

A method of evaluating the risk of floor water inrush using principal component logistic regression analysis (PCLRA) and an improved analytic hierarchy process (IAHP) is presented. The approach was validated by a case study at the Yangcheng coal mine in Shandong Province, China. First, the risk assessment index of floor water inrush was determined based on geological and hydrogeological conditions of the study area. Then, a comprehensive evaluation model (CEM), combining PCLRA with IAHP, was constructed to determine the comprehensive weight of each water-inrush evaluation index. Finally, water-inrush risk zoning was determined with GIS. The results show that the CEM, compared with the water-inrush coefficient method (WICM) traditionally and commonly used in China, has higher fitting accuracy and more detailed division of water-inrush risk areas. This method not only follows the observations in reality, but also fully considers the relative importance of water-inrush evaluation indices. The results can provide a theoretical basis for the safe mining of coal seams above confined groundwater.

Coal-floor water-inrush incidents account for a large proportion of coal mine disasters in northern China, and accurate risk assessment is crucial for safe coal production. A novel and promising assessment model for water inrush is proposed based on random forest (RF), which is a powerful intelligent machine-learning algorithm. RF has considerable advantages, including high classification accuracy and the capability to evaluate the importance of variables; in particularly, it is robust in dealing with the complicated and non-linear problems inherent in risk assessment. In this study, the proposed model is applied to Panjiayao Coal Mine, northern China. Eight factors were selected as evaluation indices according to systematic analysis of the geological conditions and a field survey of the study area. Risk assessment maps were generated based on RF, and the probabilistic neural network (PNN) model was also used for risk assessment as a comparison. The results demonstrate that the two methods are consistent in the risk assessment of water inrush at the mine, and RF shows a better performance compared to PNN with an overall accuracy higher by 6.67%. It is concluded that RF is more practicable to assess the water-inrush risk than PNN. The presented method will be helpful in avoiding water inrush and also can be extended to various engineering applications.

With depleted coal resources or deteriorating mining geological conditions, some coal mines have been abandoned in the Fengfeng mining district, China. Water that accumulates in an abandoned underground mine (goaf water) may be a hazard to neighboring mines and impact the groundwater environment. Groundwater samples at three abandoned mines (Yi, Er and Quantou mines) in the Fengfeng mining district and the underlying Ordovician limestone aquifer were collected to characterize their chemical and isotopic compositions and identify the sources of the mine water. The water was HCO₃·SO₄-Ca·Mg type in Er mine and the auxiliary shaft of Yi mine, and HCO₃·SO₄-Na type in the main shaft of Quantou mine. The isotopic compositions (δD and δ¹⁸O) of water in the three abandoned mines were close to that of Ordovician limestone groundwater. Faults in the abandoned mines were developmental, possibly facilitating inflows of groundwater from the underlying Ordovician limestone aquifers into the coal mines. Although the Sr²⁺ concentrations differed considerably, the ratios of Sr²⁺/Ca²⁺ and ⁸⁷Sr/⁸⁶Sr and the ³⁴S content of SO₄²⁻ were similar for all three mine waters and Ordovician limestone groundwater, indicating that a close hydraulic connection may exist. Geochemical and isotopic indicators suggest that (1) the mine waters may originate mainly from the Ordovician limestone groundwater inflows, and (2) the upward hydraulic gradient in the limestone aquifer may prevent its contamination by the overlying abandoned mine water. The results of this study could be useful for water resources management in this area and other similar mining areas.

Many numerical methods that simulate groundwater flow, particularly the continuous Galerkin finite element method, do not produce velocity information directly. Many algorithms have been proposed to improve the accuracy of velocity fields computed from hydraulic potentials. The differences in the streamlines generated from velocity fields obtained using different algorithms are presented in this report. The superconvergence method employed by FEFLOW, a popular commercial code, and some dual-mesh methods proposed in recent years are selected for comparison. The applications to depict hydrogeologic conditions using streamlines are used, and errors in streamlines are shown to lead to notable errors in boundary conditions, the locations of material interfaces, fluxes and conductivities. Furthermore, the effects of the procedures used in these two types of methods, including velocity integration and local conservation, are analyzed. The method of interpolating velocities across edges using fluxes is shown to be able to eliminate errors associated with refraction points that are not located along material interfaces and streamline ends at no-flow boundaries. Local conservation is shown to be a crucial property of velocity fields and can result in more accurate streamline densities. A case study involving both three-dimensional and two-dimensional cross-sectional models of a coal mine in Inner Mongolia, China, are used to support the conclusions presented.

The mining industry, especially coal mining, may severely affect the spatial and temporal evolution of groundwater. To provide a potential model outlining the hydrogeochemical evolution of groundwater as influenced by coal mining, a multi-layer groundwater system in a coal mining area was investigated. A total of 76 groundwater samples were collected between 1964 and 2018 for hydrogeochemical analysis from boreholes, underground tunnels, and surface pits at Xinglongzhuang Coal Mine in China. Hierarchical cluster analysis and principal component analysis were used to classify four significant groundwater zones and two principal components. The results showed that mining may have caused the rock strata to sink, obstructing the path linking the Permian and lower Quaternary aquifers, and resulting in intensified ion exchange in the lower Quaternary aquifer. The concentrations of Na⁺ and Ca²⁺ in the groundwater from the lower Quaternary aquifer changed over the studied period (~54 years). The gradual increase of Na⁺ and decrease of Ca²⁺ concentration verified the action of cation exchange. The four main aquifers had relatively independent hydrogeochemistry, suggesting that the hydraulic conductivity of the natural faults is weak and the sealing properties of hydrogeological drill holes in the coal field are good. Analysis of 26 heavy metals in the mine drainage water showed that there is only minor pollution after the water has been simply treated. These data analysis methods and results could be useful in areas with long-term mining to interpret the evolution of groundwater and to promote groundwater quality management.

Water inrush in coal mines is commonly linked to fault zones. Excavation of the coal seam can lead to new fractures in the associated fault zone. Many water inrush disasters have a time lag, which is closely related to the fault zone’s permeability. In the present study, three kinds of fault analog samples (artificially reproduced samples analogous to the fault material) are prepared according to microscopic characteristics of natural fault samples, and permeability tests are carried out under constant water pressure. By monitoring the pressure change during the permeability test, the seepage process in the fault zone can be divided into three stages: slow growth, rapid growth, and saturation. In addition, a time-dependent equation of porosity and permeability in porous media is introduced in the coefficient partial differential equation module in COMSOL Multiphysics. By fully coupling with the Brinkman flow module, three kinds of numerical models of the fault zone with different initial porosity and permeability are established. The porosity growth rates in the three fault-zone seepage stages are 24, 23, and 2%, respectively. The growth rates of permeability are 122, 110, and 8%, respectively. The growth rates of flow velocity are 211, 185, and 11%, respectively. The growth rate of the fault model with low porosity and low permeability is lower than that of the other two models. By discussing different conceptual models of water inrush from faults, the results indicate that water inrush disasters can be delayed or prevented if the clay content in the fault is high.