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The hydrogeochemical characteristics, water quality and health risk statuses of waters in Umunya district, southeastern Nigeria were studied, in attempt to evaluate their suitability for drinking and domestic purposes. Twelve groundwater and 3 surface water samples were analyzed for 26 physicochemical and hydrogeochemical parameters, using standard techniques. Results show that dominance of cations and anions is in the order Ca2+ > Na+ > K+ > Mg2+ and HCO3– > Cl– > NO3– > SO4–, respectively. Order of dominance of the heavy metals is Pb > Zn > Fe > Ni > Mn > Cr > Ba. Eight water types were identified, with Ca–Na–HCO3 (26.66%) and Na–Cl–HCO3 (20%) dominating the study area. All the water types characterize five major facies. Further, the result revealed that the physical properties and chemical ionic concentrations in the waters are well below standard maximum permissible limits, although majority of the samples have pH values off the allowable limits of 6.5–8.5, classing the waters as slightly acidic. Generally, the water quality in the study area is deteriorated due to the presence of high levels of heavy metals. Water quality index results show that 46.67% of the water samples are in excellent and good categories. 13.33% are in poor water category, whereas 40% are in category unsuitable for drinking purposes. A good percentage of the waters predispose users to health risks. Stoichiometric and statistical analyses revealed that the variations in chemistry and quality of the waters are due to combined influence of human activities and geogenic processes (silicate weathering and ionic exchanges). Treatment of contaminated waters before use is, therefore, recommended.

The aim of this study was to evaluate and characterize the hydrogeochemistry and quality of groundwater (for human consumption) in Ogbaru district, southeast Nigeria. Borehole samples were subjected to physicochemical, bacteriological, hydrogeochemical, and statistical analysis. The physicochemical characteristics of the water were below standard maximum permissible limits for drinking water. Moreover, heavy metals were found in low concentrations (below their permissible limits) in all of the samples. However, majority of the samples have pH values below the allowable limits of 6.5–8.5, indicating they are slightly acidic waters. The dominance of cations and anions is in the order: Ca > Mg > Na > K and HCO 3  > Cl > NO 3  > SO 4  > PO 4  > NO 2 , respectively. Mg–Ca–HCO 3 water type dominated the area, constituting about 47.4% of the total samples. Ca–Mg–HCO 3 water type constituted about 16%; Mg–Ca–Na and Ca–Mg–Na–HCO 3 water types constituted 10.5% each, whereas Ca–Mg–Cl, Mg–Ca–Cl–NO 3 , and Ca–Mg types made up 5.2% each. The possible sources and influencers (both anthropogenic and geogenic) of the physical and chemical water quality parameters were identified by correlation and principal component analyses. Although most of the groundwater samples are of good quality based on the physicochemical properties, the presence of coliforms indicates that their quality is questionable and hence not safe for drinking. Therefore, treating them before use is recommended.

High concentrations of potentially toxic elements (PTEs) in potable water can cause severe human health disorders. Present study examined the fitness of groundwater for drinking purpose based on the occurrence of nine PTEs in a heavy pilgrim and tourist influx region of the Garhwal Himalaya, India. The concentrations of analyzed PTEs in groundwater were observed in the order of Zn > Mn > As > Al > Cu > Cr > Se > Pb > Cd. Apart from Mn and As, other PTEs were within the corresponding guideline values. Spatial maps were produced to visualize the distribution of the PTEs in the area. Estimated water pollution indices and non-carcinogenic risk indicated that the investigated groundwater is safe for drinking purpose, as the hazard index was < 1 for all the water samples. Assessment of the cancer risk of Cr, As, Cd, and Pb also indicated low health risks associated with groundwater use, as the values were within the acceptable range of ≤ 1 × 10 −6 to 1 × 10 −4 . Multivariate statistical analyses were used to describe the various possible geogenic and anthropogenic sources of the PTEs in the groundwater resources although the contamination levels of the PTEs were found to pose no serious health risk. However, the present study recommends to stop the discharge of untreated wastewater and also to establish cost-effective as well as efficient water treatment facility nearby the study area. Present work’s findings are vital as they may protect the health of the massive population from contaminated water consumption. Moreover, it can help the researchers, governing authorities and water supplying agencies to take prompt and appropriate decisions for water security.

This paper quantified the level of heavy metals contamination, identified possible sources of pollution, and assessed the human health risks associated with drinking water resources in Ojoto Province, Nigeria. The study’s gross findings revealed that the suitability of some water sources for consumption purposes in this province is questionable. Based on water quality index, 57.14% of the total samples are within acceptable limits, while 42.86% are unsuitable for drinking. It was observed that the northwestern and southern parts of the study area have more of deteriorated water quality. The health hazard index revealed that 25% of the samples predispose their consumers (both adult and children populations) to high chronic health risks. Moreover, heavy metal pollution index, contamination index, and probability of cancer risk (CR) revealed that about 25% of the total samples were unsuitable and off the CR standard acceptable range of ≤ 1 × 10−6–1 × 10−4. Correlation and component factor analyses linked the origin of major ions to geogenic processes and that of the heavy metals to both natural and anthropogenic processes. Cluster analysis divided the samples into two equal classes (50% each): poor and excellent quality waters. This study indicated that Pb is the priority pollutant impacting the water quality. The various assessments revealed that waters from hand-dug wells and deeper boreholes are the least contaminated and hence best suited for drinking than waters from springs, streams, and shallow wells.

The present study was carried out using artificial neural network (ANN) model for predicting the sodium hazardness, i.e., sodium adsorption ratio (SAR), percent sodium (%Na) residual, Kelly’s ratio (KR), and residual sodium carbonate (RSC) in the groundwater of the Pratapgarh district of Southern Rajasthan, India. This study focuses on verifying the suitability of water for irrigational purpose, wherein more groundwater decline coupled with water quality problems compared to the other areas are observed. The southern part of the Rajasthan State is more populated as compared to the rest of the parts. The southern part of the Rajasthan is more populated as compared to the rest of the Rajasthan, which leads to the industrialization, urbanization, and evolutionary changes in the agricultural production in the southern region. Therefore, it is necessary to propose innovative methods for analyzing and predicting the water quality (WQ) for agricultural use. The study aims to develop an optimized artificial neural network (ANN) model to predict the sodium hazardness of groundwater for irrigation purposes. The ANN model was developed using ‘nntool’ in MATLAB software. The ANN model was trained and validated for ten years (2010–2020) of water quality data. An L-M 3-layer back propagation technique was adopted in ANN architecture to develop a reliable and accurate model for predicting the suitability of groundwater for irrigation. Furthermore, statistical performance indicators, such as RMSE, IA, R, and MBE, were used to check the consistency of ANN prediction results. The developed ANN model, i.e., ANN4 (3-12-1), ANN4 (4-15-1), ANN1 (4-5-1), and ANN4 (3-12-1), were found best suited for SAR, %Na, RSC, and KR water quality indicators for the Pratapgarh district. The performance analysis of the developed model (3-12-1) led to a correlation coefficient = 1, IA = 1, RMS = 0.14, and MBE = 0.0050. Hence, the proposed model provides a satisfactory match to the empirically generated datasets in the observed wells. This development of water quality modeling using an ANN model may help to useful for the planning of sustainable management and groundwater resources with crop suitability plans as per water quality.

Hydrogeomorphic factors were suspected to contribute to the persistent gully erosion taking place in Nanka, Ogwashi and Benin formations underlying the southern Anambra State, Nigeria. Therefore, this study investigated the impact of hydrology and geomorphology on gully development and expansion in this area using integrated field survey, hydrological, geotechnical and geomorphological approaches. Field survey and hydrological results revealed that the study area is characterized by numerous surface water bodies and shallow groundwater systems. Both the surface waters and groundwater have a westward flow direction, from areas of high elevations on the Nanka Formation to areas of low elevations on the Ogwashi and Benin formations. Geotechnical results revealed that the soils are permeable, weak, easily dispersible and collapsible. Geomorphological analysis showed that the area is characterized by uneven badland topography, high gully slope gradients, concave slopes, poor land-use practices, and low vegetation cover. Generally, the results of this study indicated that hydrogeomorphology and soil engineering properties substantially influence the gullying processes in the area. However, areas underlain by the Nanka Formation have higher gullying intensity than in areas underlain by the Ogwashi and Benin formations due to variations in their hydrogeomorphological characteristics.

There is an urgent need to explore and analyze new aquifer recharge potential zones (ARPZ) in arid regions exposed mainlyto hard rock local aquifers, whether fractured or non-fractured, for investment and fulfillment of the Saudi Vision 2030. Over-pumping, seawater intrusion, climatological changes, population growth, lack of traditional water supplies, expensive desalinized water, and excessive evaporation have characterized the Duba region of Tabuk province of Saudi Arabia (SA). Aquifer productivity and potentiality are affected by surface geology, rainfall, lineament density, drainage density, slope, elevation, soil, and normalized difference vegetation index (NDVI). This study aims to demarcate the ARPZ using integrated remote sensing and geographic information system (GIS) and (RS) approaches. The relative importance of each parameter was determined based on its impact on the aquifer’s potential through the analytical hierarchical process (AHP). The ARPZ zones are categorized into five classes starting from very low to very high potentiality. Southern, western, and northern areas have high to very high aquifer potentiality and recharge. They made up roughly 43% of the area that was examined. About 41.8% of the research area is comprised of low to very low groundwater potentiality, and this potentiality is dispersed over the western and central regions of the region. The medium aquifer potentiality level reflects about 15.2%. The high to very high aquifer potentiality areas coincide with low concentrations of total dissolved solids (TDS), electrical conductivity (EC), and nitrate (NO3). The outcomes emphasized the decisiveness of the entire study and its applicability to any place with similar groundwater aspirations and management.

Several water quality contaminants have attracted the attention of numerous researchers globally, in recent times. Although the toxicity and health risk assessments of sulfate and water hardness have not received obvious attention, nitrate contamination has gained peculiar research interest globally. In the present paper, multiple data-driven indexical, graphical, and soft computational models were integrated for a detailed assessment and predictive modeling of the contamination mechanisms, toxicity, and human health risks of natural waters in Southeast Nigeria. Majority of the tested physicochemical parameters were within their satisfactory limits for drinking and other purposes. However, total hardness (TH), SO 4 , and NO 3 were above stipulated limits in some locations. A nitrate health risk assessment revealed that certain areas present a chronic health risk to children, females, and males due to water intake. However, the dermal absorption route was found to have negligible health risks. SO 4 in some locations was above the 100 mg/L Nigerian limit; thus, heightening the potential health effects due to intake of the contaminated water resources. Most samples had low TH values, which exposes users to health defects. There are mixed contamination mechanisms in the area, according to graphical plots, R-mode hierarchical dendrogram, factor analysis, and stoichiometry. However, geogenic mechanisms predominate over human-related mechanisms. Based on the results, a composite diagrammatic model was developed. Furthermore, predictive radial basis function (RBF) and multiple linear regression (MLR) models accurately predicted the TH, SO 4 , and NO 3 , with the RBF outperforming the MLR models. Insights from the RBF and MLR models were useful in validating the results of the hierarchical dendrogram, factor, stoichiometric, and graphical analyses.

Swiftly increasing population and industrial developments of urban areas has accelerated the worsening of the water quality in recent years. Groundwater samples from different locations of the Doon valley, Garhwal Himalaya were analyzed to measure concentrations of six potential toxic elements (PTEs) viz. chromium (Cr), nickel (Ni), arsenic (As), molybdenum (Mo), cadmium (Cd), and lead (Pb) using Inductively Coupled Plasma Mass Spectrometer (ICP-MS) with the aim to study the spatial distribution and associated hazards. In addition, machine learning algorithms have been used for prediction of water quality and identification of influencing PTEs. The results inferred that the mean values (in the units of µg L −1 ) of analyzed PTEs were observed in the order of Mo (1.066) > Ni (0.744) > Pb (0.337) > As (0.186) > Cr (0.180) > Cd (0.026). The levels and computed risks of PTEs were found below the safe limits. The radial basis function neural network (RBF-NN) algorithms showed high level of accuracy in the predictions of heavy metal pollution index (HPI), heavy metal evaluation index (HEI), non-carcinogenic (N-CR) and carcinogenic (CR) parameters with determination coefficient values ranged from 0.912 to 0.976. However, the modified heavy metal pollution index (m-HPI) and contamination index (CI) predictions showed comparatively lower coefficient values as 0.753 and 0.657, respectively. The multilayer perceptron neural network (MLP-NN) demonstrated fluctuation in precision with determination coefficient between 0.167 and 0.954 for the prediction of computed indices (HPI, HEI, CI, m-HPI). In contrast, the proficiency in forecasting of non-carcinogenic and carcinogenic hazards for both sub-groups showcased coefficient values ranged from 0.887 to 0.995. As compared to each other, the radial basis function (RBF) model indicated closer alignments between predicted and actual values for pollution indices, while multilayer perceptron (MLP) model portrayed greater precision in prediction of health risk indices.

Contamination in coastal regions attributed to fluoride and nitrate cannot be disregarded, given the substantial environmental and public health issues they present worldwide. For effective decontamination, it is pivotal to identify regional pollution hotspots. This comprehensive study was performed to assess the spatial as well as indexical water quality, identify contamination sources, hotspots, and evaluate associated health risks pertaining to nitrate and fluoride in the Al-Hassa region, KSA. The physicochemical results revealed a pervasive pollution of the overall groundwater. The dominant water type was Na-Cl, indicating saltwater intrusion and reverse ion exchange impact. Spatiotemporal variations in physicochemical properties suggest diverse hydrochemical mechanisms, with geogenic factors primarily influencing groundwater chemistry. The groundwater pollution index varied between 0.8426 and 4.7172, classifying samples as moderately to very highly polluted. Similarly, the synthetic pollution index (in the range of 0.5021–4.0715) revealed that none of the samples had excellent water quality, with various degrees of pollution categories. Nitrate health quotient (HQ) values indicated chronic human health risks ranging from low to severe, with infants being the most vulnerable. Household use of nitrate-rich groundwater for showering and cleaning did not pose significant health risks. Fluoride HQ decreased with age, and children faced the highest risk of fluorosis. The hazard index (HI) yielded moderate- to high-risk values. Nitrate risks were 1.21 times higher than fluoride risks, as per average HI assessment. All samples fell into the vulnerable category based on the total hazard index (THI), with 88.89% classified as very high risk. This research provides valuable insights into groundwater quality, guiding water authorities, inhabitants, and researchers in identifying safe water sources, vulnerable regions, and human populations. The results highlight the need for appropriate treatment techniques and long-term coastal groundwater management plans.