Seasonality of hydrogeochemical evolutions and isotopic variabilities (δ18O, δ2H and d-excess) in the surface water as well as groundwater from tropical central-south Mexico.

Due to adverse impact of the global warming on hydrological resources, we intended to document the hydrogeochemical evolutions of surface and groundwater at tropical central-south Mexico in terms of seasonality of rock-water interaction, precipitation/evaporation variation and moisture source by evaluating the major ion chemistry in Piper and Gibbs plots, Durov diagram and through estimation of the chloro-alkaline indices as well as assessing the stable isotope compositions (δ18O and δ2H) in samples from different seasons of a year. Surface water of the Lake Coatetelco shifted from mostly Ca-Mg-HCO3 facies in wet summer-autumn to Na-HCO3-Cl facies in the dry spring due to elevated Na, Cl and HCO3. Greater evaporation in spring led to a maximum δ18O enrichment of ca.7‰ compared to the other seasons, and much depleted deuterium excess (-40.92‰ to -39.20‰). Interaction of the lake water with subsurface carbonate lithologies, and comparable isotopic compositions reflected the enhanced interaction between the surface water body and aquifers in the wet autumn. Effect of seasonality, however, was unclear on the groundwater facies, and its heterogenous composition (Ca-Mg-HCO3, Na-HCO3-Cl and Na-HCO3) reflected the interactions with different lithologies. Fractionations in isotope compositions of the groundwater were caused from recharge at different elevations, seasonality of moisture sources and moisture recycling. The water-mineral saturation index was an efficient proxy of seasonality as the lake water and groundwater (avg SIcalcite > 0.5) of the dry autumn were saturated with calcite. This vital information about carbonate precipitation, pCO2 and chemical facies would be useful for the better interpretation of paleoclimate archives in this region.

Evaluation of water from Lake Coatetelco in central-south Mexico and surrounding groundwater wells for drinking and irrigation, and the possible health risks.

Due to an increasing reduction of hydrological resources across Mexico and their growing contamination from global warming and anthropogenic activities, this study evaluated water from the perennial Lake Coatetelco (Ca-Mg-HCO3) in tropical central-southern Mexico and groundwater (Ca-Mg-HCO3 and Na-HCO3-Cl) from the surrounding wells for drinking as well as irrigation qualities. Comparison with the WHO guidelines and the estimated water quality indices (DWQI and IWQI) grouped almost all the samples collected after the warm season rainfall in excellent and good categories (DWQI < 100) for drinking, even though fluoride remained > 1.5 mg/L in 50% samples. Except for one groundwater sample, all showed > 25% permeability (classes I and II) in Donnen classification indicating their suitability for irrigation. USSL and Wilcox classifications, however, catalogued some in the high-salinity hazard group and some as doubtful for irrigating regular plants. Samples from about 53% wells were also in high and severe restriction categories of IWQI for the irrigation. Total Hazard Quotient Index (THQI) for estimating the non-carcinogenic risk (HQfluoride > 1) showed that at least one lake water sample and 53% of groundwater might expose the adult and child population to dental and skeletal fluorosis. This water quality assessment data posterior to the rainfall season could be useful as a baseline for both the short- and long-term monitoring in attention to the United Nation's Sustainable Development Goal 6.

Microbial contamination effects on the hydrochemical parameter in a Thettiyar watershed, Kerala, India, using GIS.

The present study has been carried out to assess the quality of groundwater and surface water resources of Thettiyar watershed, Kerala, India. Sixty-six water samples were collected during pre-monsoon (April, 2019) and monsoon (July, 2019) season, and analyzed for pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness and major cations and anions and microbiological parameters as well. According to the piper diagram's plot, Ca and Mg dominate over Na among the cations, and Cl is the most prevalent anion in groundwater throughout both the studied seasons. The hydrochemical analysis of water samples revealed that all the parameters are within the permissible limit except for pH. For microbiological analysis, the samples were tested for total coliform and fecal coliform. Most of the groundwater samples collected have higher total coliform and fecal coliform (E. coli) content than the recommended count by BIS (2012). The pre-monsoon surface water samples owned a maximum number of 3700 cfu/100 ml (TNTC-too numerous to count) of total coliform and 1400 cfu/100 ml (TNTC) of fecal coliform. In monsoon, the number of total coliform and fecal coliform has increased to 3800 cfu/100 ml and 1900 cfu/100 ml respectively. E. coli and total coliform are effectively correlated with each other in both seasons, in accordance with the statistical study. Domestic, sewage dump, and other household wastes are the main sources of bacterial contamination in the study area, which in turn nourishes contaminant organisms. According to the results, the government or municipality should implement an appropriate system for managing solid waste and should take all necessary measures to clean up the study area.

Novel machine learning algorithms to predict the groundwater vulnerability index to nitrate pollution at two levels of modeling.

The accurate mapping and assessment of groundwater vulnerability index are crucial for the preservation of groundwater resources from the possible contamination. In this research, novel intelligent predictive Machine Learning (ML) regression models of k-Neighborhood (KNN), ensemble Extremely Randomized Trees (ERT), and ensemble Bagging regression (BA) at two levels of modeling were utilized to improve DRASTIC-LU model in the Miryang aquifer located in South Korea. The predicted outputs from level 1 (KNN and ERT models) were used as inputs for ensemble bagging (BA) in level 2. The predictive groundwater pollution vulnerability index (GPVI), derived from DRASTIC-LU model was adjusted by NO3-N data and was utilized as the target data of the ML models. Hyperparameters for all models were tuned using a Grid Searching approach to determine the best effective model structures. Various statistical metrics and graphical representations were used to evaluate the superior predictive performance among ML models. Ensemble BA model in level 2 was more precise than standalone KNN and ensemble ERT models in level 1 for predicting GPVI values. Furthermore, the ensemble BA model offered suitable outcomes for the unseen data that could subsequently prevent the overfitting issue in the testing phase. Therefore, ML modeling at two levels could be an excellent approach for the proactive management of groundwater resources against contamination.

Geochemical evolution and seasonality of groundwater recharge at water-scarce southeast margin of the Chihuahuan Desert in Mexico.

Climate models for the 21st century project further reduction in the warm season precipitation and more frequent droughts across Mexico. In the possible scenario of enhanced aridity from global warming, the δ18O (-10.6 to -6.3 ‰) and δ2H (-71.1 to -57.1 ‰) compositions and deuterium-excess (0.2-14.6‰) of shallow groundwater from two different basins (Sandia and El Potosi) with similar geological and geomorphological settings were considered to evaluate the influences of early summer rainfall and later summer tropical storms on aquifers at water-scarce southeast margin of the Chihuahuan Desert. Groundwater of the Sandia Basin was recharged mainly from tropical storms. Higher CO2 partial pressure (log pCO2: -2.70 to -1.61) caused more gypsum dissolution (Ca-Mg-SO4 facies) and the effect of irrigation return flow (Ca-Mg-Cl facies) was minor. Even though the El Potosi Basin is in proximity, its groundwater was recharged from both the early and late summer precipitations. The multivariate factor analysis helped to separate the process of rock-water interactions from the recharge seasonality. Gypsum dissolution was less as the partial pressure of CO2 was comparatively lower (log pCO2: -3.01 to -2.15), and the ion exchange along with carbonate mineral dissolutions led to Ca-Mg-HCO3 facies. Over-exploitation under the condition of reduced warm season rainfall would continue to enhance the salinity of groundwater in this region. Hence, the drought mitigation policies should prioritize sustainability of the depleted aquifers and cultivation of salinity resistant crops.

Factors controlling groundwater quality in the Yeonjegu District of Busan City, Korea, using the hydrogeochemical processes and fuzzy GIS.

The hydrogeochemical processes and fuzzy GIS techniques were used to evaluate the groundwater quality in the Yeonjegu district of Busan Metropolitan City, Korea. The highest concentrations of major ions were mainly related to the local geology. The seawater intrusion into the river water and municipal contaminants were secondary contamination sources of groundwater in the study area. Factor analysis represented the contamination sources of the mineral dissolution of the host rocks and domestic influences. The Gibbs plot exhibited that the major ions were derived from the rock weathering condition. Piper's trilinear diagram showed that the groundwater quality was classified into five types of CaHCO3, NaHCO3, NaCl, CaCl2, and CaSO4 types in that order. The ionic relationship and the saturation mineral index of the ions indicated that the evaporation, dissolution, and precipitation processes controlled the groundwater chemistry. The fuzzy GIS map showed that highly contaminated groundwater occurred in the northeastern and the central parts and that the groundwater of medium quality appeared in most parts of the study area. It suggested that the groundwater quality of the study area was influenced by local geology, seawater intrusion, and municipal contaminants. This research clearly demonstrated that the geochemical analyses and fuzzy GIS method were very useful to identify the contaminant sources and the location of good groundwater quality.