Spatiotemporal successions of N, S, C, Fe, and As cycling genes in groundwater of a wetland ecosystem: Enhanced heterogeneity in wet season.

Microorganisms in wetland groundwater play an essential role in driving global biogeochemical cycles. However, largely due to the dynamics of spatiotemporal surface water-groundwater interaction, the spatiotemporal successions of biogeochemical cycling in wetland groundwater remain poorly delineated. Herein, we investigated the seasonal coevolution of hydrogeochemical variables and microbial functional genes involved in nitrogen, carbon, sulfur, iron, and arsenic cycling in groundwater within a typical wetland, located in Poyang Lake Plain, China. During the dry season, the microbial potentials for dissimilatory nitrate reduction to ammonium and ammonification were dominant, whereas the higher potentials for nitrogen fixation, denitrification, methane metabolism, and carbon fixation were identified in the wet season. A likely biogeochemical hotspot was identified in the area located in the low permeable aquifer near the lake, characterized by reducing conditions and elevated levels of Fe2+ (6.65-17.1 mg/L), NH4+ (0.57-3.98 mg/L), total organic carbon (1.02-1.99 mg/L), and functional genes. In contrast to dry season, higher dissimilarities of functional gene distribution were observed in the wet season. Multivariable statistics further indicated that the connection between the functional gene compositions and hydrogeochemical variables becomes less pronounced as the seasons transition from dry to wet. Despite this transition, Fe2+ remained the dominant driving force on gene distribution during both seasons. Gene-based co-occurrence network displayed reduced interconnectivity among coupled C-N-Fe-S cycles from the dry to the wet season, underpinning a less complex and more destabilizing occurrence pattern. The rising groundwater level may have contributed to a reduction in the stability of functional microbial communities, consequently impacting ecological functions. Our findings shed light on microbial-driven seasonal biogeochemical cycling in wetland groundwater.

Deterministic factors modulating assembly of groundwater microbial community in a nitrogen-contaminated and hydraulically-connected river-lake-floodplain ecosystem.

The river-lake-floodplain system (RLFS) undergoes intensive surface-groundwater mass and energy exchanges. Some freshwater lakes are groundwater flow-through systems, serving as sinks for nitrogen (N) entering the lake. Despite the threat of cross-nitrogen contamination, the assembly of the microbial communities in the RLFS was poorly understood. Herein, the distribution, co-occurrence, and assembly pattern of microbial community were investigated in a nitrogen-contaminated and hydraulically-connected RLFS. The results showed that nitrate was widely distributed with greater accumulation on the south than on the north side, and ammonia was accumulated in the groundwater discharge area (estuary and lakeshore). The heterotrophic nitrifying bacteria and aerobic denitrifying bacteria were distributed across the entire area. In estuary and lakeshore with low levels of oxidation-reduction potential (ORP) and high levels of total organic carbon (TOC) and ammonia, dissimilatory nitrate reduction to ammonium (DNRA) bacteria were enriched. The bacterial community had close cooperative relationships, and keystone taxa harbored nitrate reduction potentials. Combined with multivariable statistics and self-organizing map (SOM) results, ammonia, TOC, and ORP acted as drivers in the spatial evolution of the bacterial community, coincidence with the predominant deterministic processes and unique niche breadth for microbial assembly. This study provides novel insight into the traits and assembly of bacterial communities and potential nitrogen cycling capacities in RLFS groundwater.

Distribution, source investigation, and risk assessment of topsoil heavy metals in areas with intensive anthropogenic activities using the positive matrix factorization (PMF) model coupled with self-organizing map (SOM).

Over the past decade, heavy metal (HMs) contamination in soil environments has become severe worldwide. However, their resulting ecological and health risks remained elusive across a variety of soil ecosystems due to the complicated distributions and sources. This study investigated the HMs (Cr, As, Cu, Pb, Zn, Ni, Cd, and Hg) in areas with multi-mineral resources and intensive agricultural activities to study their distribution and source apportionment using a positive matrix factorization (PMF) model coupled with self-organizing map (SOM). The potential ecological and health risks were assessed in terms of distinct sources of HMs. The results disclosed that the spatial distribution of HM contaminations in the topsoil was region-dependent, primarily located in areas with high population intensity. The geo­accumulation index (Igeo) and enrichment factor (EF) values collectively displayed that the topsoils were severely contaminated by Hg, Cu, and Pb, particularly in residential farmland areas. The comprehensive analysis combined with PMF and SOM identified both geogenic and anthropogenic sources of HMs including natural, agricultural, mining, and mixed sources (caused by multi-anthropogenic factors), accounting for 24.9%, 22.6%, 45.9%, and 6.6% contribution rates, respectively. The potential ecological risk was predominantly due to the enrichment of Hg, followed by Cd. The non-carcinogenic risks were mostly below the acceptable risk level, while the potential carcinogenic health risks caused by As and Cr should be paid prime attention to, particularly for children. In addition to the 40% geogenic sources, agricultural activities contributed to 30% of the non-carcinogenic risk, whereas mining activities contributed to nearly half of the carcinogenic health risks.

Nitrogen species and microbial community coevolution along groundwater flowpath in the southwest of Poyang Lake area, China.

Nitrate and ammonia overload in groundwater can lead to eutrophication of surface water in areas where surface water is recharged by groundwater. However, this process remained elusive due to the complicated groundwater N cycling, which is governed by the co-evolution of hydrogeochemical conditions and N-cycling microbial communities. Herein, this process was studied along a generalized groundwater flowpath in Ganjing Delta, Poyang Lake area, China. From groundwater recharge to the discharge area near the lake, oxidation-reduction potential (ORP), NO3-N, and NO2-N decreased progressively, while NH3-N, total organic carbon (TOC), Fe2+, sulfide, and TOC/NO3- ratio accumulated in the lakeside samples. The anthropogenic influences such as sewage and agricultural activities drove the nitrate distribution, as observed by Cl- vs. NO3-/Cl- ratio and isotopic composition of nitrate. The hydrogeochemical evolution was intimately coupled with the changes in microbial communities. Variations in microbial community structures was significantly explained by Fe2+, NH3-N, and sulfide, while TOC/NO3- controlled the distribution of predicted N cycling gene. The absence of NH3-N in groundwater upstream was accompanied by the enrichment in Acinetobacter capable of nitrification and aerobic denitrification. These two processes were also supported by Ca2+ + Mg2+ vs. HCO3- ratio and isotopic composition of NO3-. The DNRA process downstream was revealed by both the presence of DNRA-capable microbes such as Arthrobacter and the isotopic composition of NH4+ in environments with high concentrations of NH3-N, TOC/NO3-, Fe2+, and sulfide. This coupled evolution of N cycling and microbial community sheds new light on the N biogeochemical cycle in areas where surface water is recharged by groundwater.

Spatial variability of source contributions to nitrate in regional groundwater based on the positive matrix factorization and Bayesian model.

Groundwater nitrate (NO3-) pollution has attracted widespread attention; however, accurately evaluating the sources of NO3- and their contribution patterns in regional groundwater is difficult in areas with multiple sources and complex hydrogeological conditions. In this study, 161 groundwater samples were collected from the Poyang Lake Basin for hydrochemical and dual NO3- isotope analyses to explore the sources of NO3- and their spatial contribution using the Positive Matrix Factorization (PMF) and Bayesian stable isotope mixing (MixSIAR) models. The results revealed that the enrichment of NO3- in groundwater was primarily attributed to sewage/manure (SM), which accounted for more than 50 %. The contributions of nitrogen fertilizer and soil organic nitrogen should also be considered. Groundwater NO3- sources showed obvious spatial differences in contributions. Regions with large contributions of SM (>90 %) were located in the southeastern part of the study area and downstream of Nanchang, which are areas with relatively high population density. Nitrogen fertilizer and soil organic nitrogen showed concentrated contributions in paddy soil in the lower reaches of the Gan and Rao Rivers, and these accumulations were mainly driven by the soil type, land use type, and topography. This study provides insight into groundwater NO3- contamination on a regional scale.

Spatial distribution and driving factors of groundwater chemistry and pollution in an oil production region in the Northwest China.

Concerns have been raised on the deterioration of groundwater quality associated with anthropogenic impacts such as oil extraction and overuse of fertilizers. However, it is still difficult to identify groundwater chemistry/pollution and driving forces in regional scale since both natural and anthropogenic factors are spatially complex. This study, combining self-organizing map (SOM, combined with K-means algorithm) and principal component analysis (PCA), attempted to characterize the spatial variability and driving factors of shallow groundwater hydrochemistry in Yan'an area of Northwest China where diverse land use types (e.g., various oil production sites and agriculture lands) coexist. Based on the major and trace elements (e.g., Ba, Sr, Br, Li) and total petroleum hydrocarbons (TPH), groundwater samples were classified into four clusters with obvious geographical and hydrochemical characteristics by using SOM - K-means clustering: heavily oil-contaminated groundwater (Cluster 1), slightly oil-contaminated groundwater (Cluster 2), least-polluted groundwater (Cluster 3) and NO3- contaminated groundwater (Cluster 4). Noteworthily, Cluster 1, located in a river valley with long-term oil exploitation, had the highest levels of TPH and potentially toxic elements (Ba, Sr). Multivariate analysis combined with ion ratios analysis were used to determine the causes of these clusters. The results revealed that the hydrochemical compositions in Cluster 1 were mainly caused by the oil-related produced water intrusion into the upper aquifer. The elevated NO3- concentrations in Cluster 4 were induced by agricultural activities. Water-rock interactions (e.g., carbonate as well as silicate dissolution and precipitation) also shaped the chemical constituents of groundwater in clusters 2, 3, and 4. In addition, SO42--related processes (redox, precipitation of sulfate minerals) also affected groundwater chemical compositions in Cluster 1. This work provides the insight into the driving factors of groundwater chemistry and pollution which could contribute to groundwater sustainable management and protection in this area and other oil extraction areas.

Hydrochemical and isotopic fingerprints of groundwater origin and evolution in the Urangulan River basin, China's Loess Plateau.

The origin and evolution of groundwater in the Urangulan River basin area under growing concern as its situated in an economically and ecologically crucial area of China. In the present study, a combination of different methods (i.e. self-organizing maps (SOM), piper diagrams, ionic ratios, multiple isotopic analyses and Bayesian isotope mixing model) provided an efficient way for analysing groundwater origin and evolution. The hydrochemical type was found to be Ca-HCO3 in low TDS and Na + K-Cl or Na + K-SO4 in high TDS groundwater. According to the δ2H and δ18Owater values, groundwater in the study area mainly originated from atmospheric precipitation and was influenced by evaporation. In addition, the rock weathering in conjunction with the cation exchange completely dominated the geochemical evolution process. The dual SO42- isotope and Bayesian isotope mixing model showed that gypsum dissolution, fertilizer input and sewage input were the main sources of SO42- in the study area, accounting for an average of 30.2 %, 28.5 %, and 17.3 % of SO42- in the groundwater, respectively. Other than water-rock interactions, human activity (mining and irrigation) distributed throughout the study area in combination with the spatial characteristics was the dominant factor controlling the hydrochemical evolution. The results of this study provided a basis for understanding groundwater origin and evolution while facilitating the effective management and utilization of groundwater.

Source and evolution of sulfate in the multi-layer groundwater system in an abandoned mine-Insight from stable isotopes and Bayesian isotope mixing model.

The source and evolution of sulfate (SO42-) in groundwater from abandoned mines are widely concerned environmental issues. Herein, major dissolved ions, multi-isotopes (δ34S, δ18Osulfate, δ2H and δ18Owater), machine learning (Self-organizing maps) and Bayesian isotope mixing model were used to identify the source and evolution of SO42- in an abandoned mine (Fengfeng mine, northern China) with a multi-layer groundwater system. Groundwater in the study area was mainly divided into three clusters (Cluster I, Cluster II and Cluster III), dominated by Na-SO4, Ca-SO4 and Ca-HCO3 types, respectively. According to δ2H and δ18Owater, groundwater in the study area mainly originated from atmospheric precipitation. δ34S, δ18Osulfate and SO42- suggested that bacterial sulfate reduction did not affect the SO42- isotopic composition. Dual SO42- isotopes, and MixSIAR model revealed that the main source of SO42- in the study area was pyrite oxidation/gypsum dissolution, accounting for an average of 57.4 % (gypsum), 71.24 % (pyrite oxidation) and 52.93 % (pyrite oxidation) of SO42- in the samples of Clusters I-III, respectively. Combined with the hydrochemical diagrams, the evolution of SO42- in different clusters of samples was derived. Cluster I was mainly gypsum dissolution; In contrast, Clusters II and III were mainly pyrite oxidation accompanied by carbonate dissolution, and Cluster II was also influenced by cation exchange. These findings will help in developing management strategies for protecting groundwater quality, which will provide a reference for the study of solute sources and S cycling in abandoned mines.

Hydrogeochemical evolution induced by long-term mining activities in a multi-aquifer system in the mining area.

The hydrogeochemical evolution of groundwater is related to and affected by long-term mining activities, which may deteriorate the quality of groundwater. The Fengfeng mine in Handan, North China has a 30-y history of coal mining with long-term mining activities and complex geological conditions, resulting in a complex hydrogeochemical environment in the mining region. In this study, the hydrogeochemical evolution mechanism of groundwater in a multi-aquifer system in the Fengfeng Mining Area was investigated using machine learning (self-organizing maps combined with K-means clustering) and sulfur and oxygen isotopes (δ34SSO4 and δ18OSO4). The hydrogeochemical characteristics of different aquifers in the mining area changed to different degrees after mining compared with the characteristics before mining. The spatiotemporal variations in groundwater components were found to be controlled by pyrite oxidation, gypsum dissolution, and carbonate dissolution, which are affected by mining activities. Pyrite oxidation primarily occurred in the Carboniferous thin-layer limestone aquifer (CLA) and Permian sandstone aquifer (PSA). The hydrogeochemical evolution in the Ordovician limestone aquifer (OLA), the main aquifer in the study area, was affected by leakage recharge from CLA and PSA caused by mining activities. The results showed that owing to the effects of long-term mining, the altered groundwater flow system affected the evolution of groundwater components in each aquifer, particularly the sulfate concentration. This study reveals a distinct hydrogeochemical evolution induced by mining activities, which can provide a basis for groundwater resource management in mining areas.

Geochemical fingerprint and spatial pattern of mine water quality in the Shaanxi-Inner Mongolia Coal Mine Base, Northwest China.

The spatial distribution of mine water quality and geochemical controls must be investigated for water safety and ecosystem protection in Shaanxi-Inner Mongolian Coal Mine Base (SICMB). Based on 122 mine water samples collected from 14 mining areas, self-organizing maps (SOM) combining with principal component analysis (PCA) derived that the mine water samples were classified into seven clusters. Clusters 1 and 3 (C1 and C3) samples were dominant by HCO3-Ca and mixed types, which were distributed in the recharge area of the middle SICMB. In this area, the active groundwater circulation contributed to the good water quality. Cluster 2 (C2) samples were characterized by HCO3-Na type, mainly distributed in the discharge area of the middle SICMB. These samples were threatened by heavy fluorine contamination and high residual sodium carbonate (RSC) because of slow groundwater flow in this area. Clusters 4 and 5 (C4 and C5) samples, distributed in the northeast and middle SICMB, were characterized by high Cl- concentration and light fluorine contamination. They were influenced by anthropogenic input through faults or underground mining. In contrast, Clusters 6 and 7 (C6 and C7) samples with high salinity and sulfate were distributed in the southwest SICMB. The deep groundwater circulation enhanced water-rock interaction and contributed to poor water quality. These findings are beneficial to the management of mine water resources in the SICMB and provide an insight to investigate the mine water quality in large spatial scale.