Multivariate Statistical Analysis of Hydrochemical Data and Stable Isotopes of Groundwater Contaminated with Nitrate at Huay Sai Royal Development Study Center and Adjacent Areas in Phetchaburi Province, Thailand

Groundwater pollutants characterization by geochemometric technique and geochemical modeling in tropical savanna watershed

Multiple interactions of geogenic and anthropogenic activities can trigger groundwater pollution in the tropical savanna watershed. These interactions and resultant contamination have been studied using applied geochemical modeling, conventional hydrochemical plots, and multivariate geochemometric methods, and the results are presented in this paper. The high alkalinity values recorded for the studied groundwater samples might emanate from the leaching of carbonate soil derived from limestone coupled with low rainfall and high temperature in the area. The principal component analysis (PCA) unveils three components with an eigenvalue > 1 and a total dataset variance of 67.37%; this implies that the temporary hardness of the groundwater and water-rock interaction with evaporite minerals (gypsum, halite, calcite, and trona) is the dominant factor affecting groundwater geochemistry. Likewise, the PCA revealed anthropogenic contamination by discharging [Formula: see text] [Formula: see text][Formula: see text] and [Formula: see text] from agricultural activities and probable sewage leakages. Hierarchical cluster analysis (HCA) also revealed three clusters; cluster I reflects the dissolution of gypsum and halite with a high elevated load of [Formula: see text] released by anthropogenic activities. However, cluster II exhibited high [Formula: see text] and [Formula: see text] loading in the groundwater from weathering of bicarbonate and sylvite minerals. Sulfate ([Formula: see text]) dominated cluster III mineralogy resulting from weathering of anhydrite. The three clusters in the Maiganga watershed indicated anhydrite, gypsum, and halite undersaturation. These results suggest that combined anthropogenic and natural processes in the study area are linked with saturation indexes that regulate the modification of groundwater quality.

Determination of conditioning factors for mapping nickel contamination susceptibility in groundwater in Kanchanaburi Province, Thailand, using random forest and maximum entropy

Groundwater pollution from nickel (Ni) has been a severe concern in Kanchanaburi Province, Thailand. Recent assessments revealed that the Ni concentration in groundwater, particularly in urban areas, often exceeded the permissible limit. The challenge for groundwater agencies is therefore to delineate regions with high susceptibility to Ni contamination. In this study, a novel modeling approach was applied to a dataset of 117 groundwater samples collected from Kanchanaburi Province between April and July 2021. Twenty site-specific initial variables were considered as influencing factors to Ni contamination. The Random Forest (RF) algorithm with Recursive Feature Elimination (RFE) function was used to select the fourteen most influencing variables. These variables were then used as input features to train a ME model to delineate the Ni contamination susceptibility at a high confidence (Area Under the Curve (AUC) validation value of 0.845). Ten input variables of the altitude, geology, land use, slope, soil type, distance to industrial areas, distance to mining areas, electric conductivity, oxidation-reduction potential, and groundwater depth were discovered in the most explaining the variation of spatial Ni contamination at very high (95.47 km²) and high (86.65 km²) susceptibility. This study devises the novel machine learning approach to identify the conditioning factors and map Ni contamination susceptibility in the groundwater, which provides a baseline dataset and reliable methods for the development of a sustainable groundwater management strategy.

Groundwater quality and vulnerability in farms from agricultural-dairy basin of the Argentine Pampas

Agricultural and livestock activities strongly influence groundwater quality and conditioning its use as water supply in rural areas. The aim was to determine the quality and suitability of the groundwater supply used in dairy farms of an agricultural area of Pampa plain of Córdoba (Argentina). Piper's diagram showed that the groundwater types were sodium bicarbonate, sodium bicarbonate-chloride, sodium chloride-sulfate, and sodium sulfate. Physicochemical parameters revealed that cations and anions showed a high and significant correlation in water samples, indicating a strong water-rock interaction. Nitrate (NO₃^-) content was significantly correlated with pH, water well depth, and distance from contamination sources. A high positive correlation between arsenic (As) and bicarbonate, sulfate, sodium, and chloride (p < 0.05) indicates a similar origin. Among the pesticides monitored, 2,4-D was detected in 25% of groundwater samples (0.4 to 0.8 µg/L) coinciding with the ordinary application practices. In general, most of the groundwater samples did not comply with national and international regulations for drinking water and dairy hygiene, due to the high content of As, NO₃^-, bacteria, and the presence of 2,4-D herbicide. However, the quality of water was suitable for livestock drink. The data obtained in this study contribute to a better understanding of the contamination processes taking place and improve the agricultural and livestock management for an efficient use of this resource by dairy farmers.

Spatial distribution and health risk assessment of As and Pb contamination in the groundwater of Rayong Province, Thailand

This study investigates the presence of arsenic (As) and lead (Pb) in groundwater and their spatial distribution in Ban Khai District, Rayong Province, Thailand. Forty groundwater samples were collected at different locations in the dry and wet seasons during March and August of 2019, respectively. The hydrochemical facies illustrate that the major groundwater types in both seasons mainly consisted of Ca-Na-HCO_3, Ca-HCO₃-Cl and Na-HCO₃ types. The concentration of As ranged from <0.300 to 183.00 μg/L, accounting for 22% (18 of 80 samples), exceeding the WHO guidelines of 10 μg/L. The spatial distribution of As was distinctly predominant as a hot spot in some areas during the wet season. The wells may have been contaminated from human activity and thus constituted a point source in the adjacent area. For Pb, its concentration in all the wells were not exceeded 10 μg/L of the WHO guidelines, appearing as a background concentration in this area. Most of the wells were shown to be in an oxidation state, supporting As^V mobility. Moreover, the area also had a nearly neutral pH that promoted As^V desorption, while the presence of undissolved Pb in the aquifers tended to increase. Furthermore, chemical applications to agricultural processes could release the As composition into the groundwater. The health risk resulting from oral consumption was at a higher risk level than dermal contact. The non-carcinogenic risk affecting the adult population exceeded the threshold level by approximately 27.5% of the wells, while for the children group, the risk level was within the limit. Total cancer risk (TCR) of adult residents exceeded the acceptable risk level (1 × 10^-6) in all wells, causing carcinogenic health effects. Therefore, health surveillance is important in monitoring the toxic effects on the local residents who use groundwater from these contaminated wells. Furthermore, a sanitation service and an alternative treatment of the water supply will be needed, especially in wells with high As levels.

Acid mine drainage potential of waste rocks in a gold mine (Thailand): application of a weathering cell test and multivariate statistical analysis

In the process of gold mining, large amounts of broken waste rocks are produced and left at the surface under atmospheric conditions, which may generate acid mine drainage (AMD). This study aimed to predict the AMD generation potential and determine the concentrations of potentially toxic metals at three dump sites for a gold mine in Thailand. The AMD generation potentials of waste rock samples collected from the oxide, transition and sulfide dump sites was determined using the weathering cell test. The kinetic test had a 7-d cycle and was run for ~ 21 cycles; the effluent pH, conductivity, redox potential and levels of sulfate, and major and trace metals (i.e., As, Co, Cu, Fe, Mn, Pb and Zn) present in each cycle were measured. Some samples generated significant amounts of AMD, especially the massive sulfide samples from the transition and sulfide dump sites. The effluent water pH in the oxide and sulfide dump sites was neutral to slightly alkaline (pH ~ 6-9), while it was acidic to neutral (pH ~ 3-7) in the transition dump site. The transition dump site samples generated significantly higher acidity and sulfate levels than those from the oxide and sulfide dump sites. Furthermore, some waste rock samples, including the massive sulfide from the transition dump site, released relatively high amounts of heavy metals; in addition, sulfate reached levels (9.48 mg kg^-1 of waste rock) high enough to pose a risk to ecosystems. The long-term acid generation suggested that some waste rock samples from sulfide dump site and transition dump site will continue to generate acid for long periods. Based on data from the weathering cell test and multivariate statistical analysis, the transition dump site potentially generates a lower pH leachate than other waste rock dumps.

Identification of the Dominant Factors in Groundwater Recharge Process, Using Multivariate Statistical Approaches in a Semi-Arid Region

Identifying contributing factors of potential recharge zones is essential for sustainable groundwater resources management in arid regions. In this study, a data matrix with 66 observations of climatic, hydrogeological, morphological, and land use variables was analyzed. The dominant factors in groundwater recharge process and potential recharge zones were evaluated using K-means clustering, principal component analysis (PCA), and geostatistical analysis. The study highlights the importance of multivariate methods coupled with geospatial analysis to identify the main factors contributing to recharge processes and delineate potential groundwater recharge areas. Potential recharge zones were defined into cluster 1 and cluster 3; these were classified as low potential for recharge. Cluster 2 was classified with high potential for groundwater recharge. Cluster 1 is located on a flat land surface with nearby faults and it is mostly composed of ignimbrites and volcanic rocks of low hydraulic conductivity (K). Cluster 2 is located on a flat lowland agricultural area, and it is mainly composed of alluvium that contributes to a higher hydraulic conductivity. Cluster 3 is located on steep slopes with nearby faults and is formed of rhyolite and ignimbrite with interbedded layers of volcanic rocks of low hydraulic conductivity. PCA disclosed that groundwater recharge processes are controlled by geology, K, temperature, precipitation, potential evapotranspiration (PET), humidity, and land use. Infiltration processes are restricted by low hydraulic conductivity, as well as ignimbrites and volcanic rocks of low porosity. This study demonstrates that given the climatic and geological conditions found in the Sierra de San Miguelito Volcanic Complex (SSMVC), this region is not working optimally as a water recharge zone towards the deep aquifer of the San Luis Potosí Valley (SLPV). This methodology will be useful for water resource managers to develop strategies to identify and define priority recharge areas with greater certainty.

Spatial Characteristics of Groundwater Chemistry in Unzen, Nagasaki, Japan

Nitrate pollution in groundwater is a serious problem in Shimabara Peninsula, Nagasaki, Japan. A better understanding of the hydrogeochemical evolution of groundwater in vulnerable aquifers is important for health and environment. In this study, groundwater samples were collected at 12 residential and 57 municipal water supply wells and springs in July and August 2018. Nitrate (NO3−N) concentration at eight sampling sites (12%) exceeded Japanese drinking water standard for NO3 + NO2−N (10 mg L−1). The highest nitrate concentration was 19.9 mg L−1. Polluted groundwater is distributed in northeastern, northwestern, and southwestern areas, where land is used for intensive agriculture. Correlation analysis suggests that nitrate sources are agricultural fertilizers and livestock waste. Dominant groundwater chemistry is (Ca+Mg)−HCO3 or (Ca+Mg)−(SO4+NO3) type. Groundwater with higher nitrate concentration is of (Ca+Mg)−(SO4+NO3) type, indicating nitrate pollution affecting water chemistry. Principal component analysis extracted two important factors controlling water chemistry. The first principal component explained dissolved ions through water–rock interaction and agricultural activities. The second principal component explained cation exchange and dominant agricultural effects from fertilizers. Hierarchical cluster analysis classified groundwater into four groups. One of these is related to the dissolution of major ions. The other three represent nitrate pollution.

Microbial community structure in aquifers associated with arsenic: analysis of 16S rRNA and arsenite oxidase genes

The microbiomes of deep and shallow aquifers located in an agricultural area, impacted by an old tin mine, were explored to understand spatial variation in microbial community structures and identify environmental factors influencing microbial distribution patterns through the analysis of 16S rRNA and aioA genes. Although Proteobacteria, Cyanobacteria, Actinobacteria, Patescibacteria, Bacteroidetes, and Epsilonbacteraeota were widespread across the analyzed aquifers, the dominant taxa found in each aquifer were unique. The co-dominance of Burkholderiaceae and Gallionellaceae potentially controlled arsenic immobilization in the aquifers. Analysis of the aioA gene suggested that arsenite-oxidizing bacteria phylogenetically associated with Alpha-, Beta-, and Gamma proteobacteria were present at low abundance (0.85 to 37.13%) and were more prevalent in shallow aquifers and surface water. The concentrations of dissolved oxygen and total phosphorus significantly governed the microbiomes analyzed in this study, while the combination of NO₃ ^--N concentration and oxidation-reduction potential significantly influenced the diversity and abundance of arsenite-oxidizing bacteria in the aquifers. The knowledge of microbial community structures and functions in relation to deep and shallow aquifers is required for further development of sustainable aquifer management.

Mechanisms of arsenic contamination associated with hydrochemical characteristics in coastal alluvial aquifers using multivariate statistical technique and hydrogeochemical modeling: a case study in Rayong province, eastern Thailand

The rapid development of Rayong Province has resulted in increased demands on groundwater usage. This has potentially induced the release of contaminants such as arsenic (As), among others (i.e., NO₃^-, PO₄^3-) from various land use types-especially in intensive agricultural areas and heavy industrial areas, including landfill sites. The objectives of this research are to investigate the As speciation and groundwater chemistry occurring due to different hydrogeological settings and the influence of human activities and to explain the mechanism of As release in the coastal alluvial aquifers in Rayong Province using multivariate statistical techniques and hydrogeochemical modeling (PHREEQC). Six major water facies, mainly consisting of Ca-Na-HCO₃-Cl and Ca-Na-Cl, were included in the hydrochemical analysis. Arsenic levels were inversely correlated with NO₃^-, SO₄^2-, DO, and ORP, confirming the reducing environment in the groundwater system. The results from the PHREEQC model show that most wells were strongly under-supersaturated with respect to arsenorite, scorodite, and arsenic pentoxide. Arsenic (As) is probably derived from the dissolution of Fe oxide and hydroxide (i.e., Fe(OH)₃, goethite, maghemite, and magnetite). The multivariate statistical techniques revealed that the As species mainly consisted of As(III), governed by the reducing environment, while As(V) may be desorbed from Fe oxide and hydroxide as the pH increases. Anthropogenic inputs and intensive pumping may enhance the reducing environment, facilitating the release of As(III) into the groundwater. The knowledge gained from this study helps to better understand the mechanisms of As contamination in coastal groundwater aquifers, which is useful for groundwater management, including the optimum pumping rate and long-term monitoring of groundwater quality.