Risk assessment of nitrate groundwater contamination using GIS-based machine learning methods: A case study in the northern Anhui plain, China.

Long-term agricultural activities have affected the sustainable development of groundwater in the Northern Anhui Plain, East China. It is, therefore, important to identify areas at high groundwater pollution risk in the Northern Anhui Plain to ensure effective protection of regional water resources. In this study, 60 groundwater samples were collected from the shallow aquifer of the plain and analyzed for nitrate (NO3-) concentrations. In addition, 10 environmental and geological factors including the elevations, distances-to-rivers, slope angles, orientations of slopes, land cover types, topographic wetness index (TWI), geomorphology, lithology, soil types, and precipitation amounts in the study area were selected as input layers. The light gradient boosting machine (LightGBM) and random forest (RF) algorithms, combined with the geographic information system (GIS), were performed to generate the groundwater pollution occurrence probability maps. The descriptive statistics showed that the NO3- concentrations in the shallow groundwater ranged from 4.3 to 73.6 mg/L. Most sampling wells exhibited NO3- concentrations above the threshold of 18.3 mg/L. The prediction results of the LightGBM and RF algorithms indicated a high groundwater NO3- pollution risk in the southern part of the plain. However, the LightGBM algorithm had a better prediction performance than RF, with a higher Kappa value of 0.84. Moreover, the frequency ratio method revealed that the precipitation amounts contributed to the groundwater NO3- pollution risk in the study area by 38.14%, followed by the elevations, slope angles, TWI, land cover types, and slope aspects, with contributions of 21.4, 13.02, 8.37, 7.44, and 6.51%, respectively. In the future, sampling of additional wells and further anthropogenic factors shall be considered for the development of more effective groundwater nitrate pollution prevention strategies provided to decision makers.

Multiple stable isotopes and geochemical approaches to elucidate groundwater reactive transport paths in mining cities: A case from the northern Anhui, China.

Mining cities are ecotone areas where human and natural components interact. Indeed, the negative effects of mining activities on drinking water quality have become a serious public concern worldwide. To elucidate groundwater genesis and reactive transport path controlling the water pollution, a multi-bodies system in the Sunan Mine area in China was considered in this study. The results of the mineral phase characterizations, hydrochemical analysis, and multiple stable isotopes (δ2H/δ18O, δ34S and 87Sr/86Sr) indicated that calcite, dolomite, gypsum, quartz, halite, organic carbon, and gases (O2, CO2 and H2O) were the primary reactants in the aquifer system, accompanied by dissolution and precipitation of minerals, cation exchange, desulfation, and evaporation. An inverse hydrogeochemical model was employed to identify three paths, Path 1 demonstrated that mine water mainly originated from the Quaternary loose aquifer water (QLA), Permian fractured sandstone aquifer water (PFA), and Carbonifer fractured limestone aquifer water (CFA), accompanied by high K++Na+ and HCO3- concentrations due to the carbonate dissolution, halite dissolution, and cation exchange processes. Path 2 showed that the recharge of the CFA and Ordovician fractured limestone aquifer (OFA) occurred from the shallow recharge zone to the deeper OFA water through faults and fractures, mainly involving halite dissolution, carbonate dissolution, and gypsum dissolution. Path 3 demonstrated the interaction between the Hui River, collapsed pond water, and QLA, accompanied by gypsum dissolution, calcite dissolution, and cation exchange. Although the shallow QLA quality met the WHO drinking water standards, the pollution risk from the surface collapse pit water cannot be ignored. Therefore, effective approaches need to be considered in the study area to reduce the connection between the collapse pit water and QLA. The study results can help decision makers to predict water quality of complex water systems in ecotone areas and other similar regions worldwide.

Groundwater pollution source identification and health risk assessment in the North Anhui Plain, eastern China: Insights from positive matrix factorization and Monte Carlo simulation.

Groundwater contaminants from natural and anthropogenic sources pose a serious threat to the ecological environment and public health. In this study, 30 groundwater samples were collected from shallow wells at a large central water source in the North Anhui Plain, eastern China. Hydrogeochemical methods, positive matrix factorization (PMF) model, and Monte Carlo simulation were used to determine the characteristics, sources, and human health risks of inorganic and organic analytes in groundwater. The groundwater was weakly alkaline with high total hardness and was dominated by HCO3-Mg·Ca, HCO3-Ca·Mg, and HCO3-Ca·Mg·Na hydrochemical facies. The concentration of naphthalene was at a safe level, while the concentrations of F-, NO3- and Mn in 16.7 %, 26.7 % and 40 % of the samples, respectively, exceeded threshold risk-based values based on Chinese groundwater quality standards. Hydrogeochemical methods revealed that water-rock interactions (including weathering of silicate minerals, dissolution of carbonates, and cation exchange), acidity, and runoff conditions control the migration and enrichment of these analytes in groundwater. The PMF model indicated that local geogenic processes, hydrogeochemical evolution, agricultural activities, and petroleum-related industrial sources were the main factors affecting groundwater quality, with contributions of 38.2 %, 33.7 %, 17.8 %, and 10.3 %, respectively. A health risk evaluation model based on Monte Carlo simulation indicated that 77.9 % of children were exposed to a total noncarcinogenic risk above safe thresholds, about 3.4 times higher than the risk to adults. The main contributor to human health risk was F- originating from geogenic processes; thus, F- was identified as a priority for control. This study demonstrates the feasibility and reliability of combining source apportionment techniques and health risk assessment to evaluate groundwater quality.

Characterizing spatial dependence of boron, arsenic, and other trace elements for Permian groundwater in Northern Anhui plain coal mining area, China, using spatial autocorrelation index and geostatistics.

Anthropogenic and geological factors play an essential role in the variability of groundwater quality, resulting in a weak spatial dependence of groundwater trace elements. Thus, it is an essential study to investigate the factors affecting groundwater quality and its spatial abundance of trace elements (including As, B, and other metalloids). In this study, samples are obtained from a Permian sandstone fracture aquifer in a coal mining area. A multivariate statistical analysis, hydrogeochemistry modeling, and spatial autocorrelation analysis were used to analyze the data. The results showed that Moran index was positive for all trace elements, which had good spatial autocorrelation. The Local indicators of spatial association (LISA) indicated that trace elements were clustered. The hydrogeochemical modeling results indicated that the precipitation and stability of iron-phase minerals, such as rhodochrosite and arsenic (As) absorption on the surface of iron-phase minerals in the aquifer, may limit concentrations in the southern region. The spatial autocorrelations of both As and Boron (B) were positive (high-high) in the western areas, indicating that As contamination occurred from both natural geological causes and human coal mining activities. In contrast, B contamination was mainly linked to the influence of human agricultural or industrial activities. Over 96% of the groundwater concentrations of As (10 µg/L) and B (300 µg/L) in the study area exceeded World Health Organization (WHO) limits. Overall, the results of this work could help decision-makers involved in regional water quality management visualize disperse zones where specific anthropogenic and geological processes may threaten groundwater quality.

Source apportionment and ecological health risks assessment from major ions, metalloids and trace elements in multi-aquifer groundwater near the Sunan mine area, Eastern China.

Evaluating the ecological health risks created by major ions, metalloids and trace elements concentrations in groundwater and pollution sources were essential to effectively protect groundwater resources. For this study, A total of 93 samples were collected from multiple aquifers in the Sunan mining area, eastern China. The Positive matrix factorization (PMF) model results revealed the following sources, in percentages. The Quaternary loose aquifer (QLA) water includes CaMg mineral dissolution (30.3 %), salinity (28.2 %), metal industrial wastewater (26.3 %), iron and manganese minerals (8.0 %) and coal gangue (7.2 %). The Permian fractured sandstone aquifer (PFA) water includes CaMg mineral dissolution sources (29.8 %), mine wastewater (28.6 %), aluminosilicate (21.6 %) and pyrite source (20.0 %). The Carbonifer fractured limestone aquifer (CFA) water includes and mine wastewater (34.2 %), CaMg mineral dissolution (25.4 %), pyrite (22.6 %) and aluminosilicate (17.7 %). The Ordovician fractured limestone aquifer (OFA) water includes manganese and aluminum metal minerals (27.9 %), halite dissolution materials (24.9 %), industrial and agricultural waste water (24.0 %) and calcium­magnesium minerals (23.2 %). A PMF-based assessment of ecological health risk indicates that the concentrations of elements As and Co are the dominant elements impacting non-carcinogenic and carcinogenic risks; and As, Cr, and Cu are the dominant elements impacting potential ecological risks. These mainly originate from geological sources, coal gangue sources, mine drainage sources and agricultural sewage discharge sources. The study showed the sources of groundwater pollution in multiple aquifers and their priority treatment areas, providing a basis for groundwater management and protection.

Hydrogeochemical Processes and Connection of Multi-Layer Groundwater System in Sunan Mining Area, Eastern China.

Groundwater is an important freshwater resource in the world and serves as the main source of water for mining areas in Northern China. Coal mining may cause changes in water quality. As such, to identify ways to prevent water contamination, this study investigates the hydrogeochemical processes and transport paths of a complex aquifer system in the Sunan mining area in Northern China. Using the APFS-MLR model, a geographic information system (GIS) spatial analysis, and a hydrochemical correlation analysis method, this study identifies the potential mineral phases in groundwater, the spatial distribution of mineral reactions, and the contribution rate of these reactions to hydrochemical variables. Inverse modeling is used to verify hydrogeochemical process. The study reveals the relationship between multiple aquifers and four hydrological transport paths. Here, Path 1 and Path 2 show that the Quaternary aquifer, Carboniferous aquifer, and Ordovician aquifer are recharging the Permian aquifer through mineral dissolution and precipitation, cation exchange, and sulfate reduction. On the other hand, Path 3 and Path 4 show that tthe connections of Carboniferous and Ordovician limestone aquifers are dominated by the dissolution and precipitation of minerals and cation exchange, and that they are mainly recharged by the Quaternary aquifer. In the future, the water level of the Permian aquifer may rise somewhat after mining ends, and the mixing of water from the Permian aquifer, Quaternary aquifer, Carboniferous aquifer, and Ordovician aquifer could cause cross-pollution. In addition, sewage produced by human activities may recharge the deep water through the shallow water, polluting the deep karst water. As such, measures should be taken to reduce the hydraulic connection between Permian mine water and karst aquifers. The results of this study may benefit water quality predictions and treatment approaches in other complex multi-layer aquifer areas in the world.

Statistical analyses of hydrochemistry in multi-aquifers of the Pansan coalmine, Huainan coalfield, China: implications for water-rock interaction and hydraulic connection.

Understanding the groundwater hydrogeochemical processes and aquifer hydraulic connections are essential for effective prevention of water inrush in concealed coal mines. In this study, 40 groundwater samples were collected from the loose layer aquifer (LA), coal measure aquifer (CA), and limestone aquifer (LA) in the Pansan coal mine, Huanan coalfield, China, and the major ion concentrations were analyzed by bivariate diagrams (Na+ + K+ - Cl- versus Ca2+ + Mg2+ - SO4 2- - HCO3 - and CAI-I versus CAI-II), multivariate statistical methods, and receptor model in order to identify the water-rock interactions and aquifer hydraulic connections. Piper diagram showed that groundwater in LA and TA was dominated by the Na-Cl type, while groundwater in CA was mainly of the Na-HCO3 type. Based on the results of bivariate diagrams and PCA/FA, weathering of silicate minerals and cation exchange (source 1), sulfate dissolution (source 2) and chloride dissolution (source 3) were the main processes controlling the groundwater chemistry. Unmix model revealed that the mean contribution of source 1 to CA samples was 74%, while LA and TA samples have higher contributions from evaporite dissolution (source 2 and source 3) relative to CA samples. Moreover, both clustering analysis methods (Q-type hierarchical and K-means cluster) confirmed the existence of a hydraulic connection between LA and TA in the northeastern part of the study area. It is concluded that the application of multivariate statistical analysis to interpret groundwater chemistry can provide useful guidance to prevent water inrush in coal mines.