The hydrogeochemical signatures, quality indices and health risk assessment of water resources in Umunya district, southeast Nigeria

Abstract 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

Assessment of PTEs in water resources by integrating HHRISK code, water quality indices, multivariate statistics, and ANNs

The use of contaminated water for drinking and sanitary purposes can be detrimental to human health. In this article, the Human Health Risk (HHRISK) code was applied, alongside the modified heavy metal index (MHMI), synthetic pollution index (SPI), and entropy-weighted water quality index (EWQI), to investigate the pollution status, ingestion, and dermal health risks of potentially toxic elements (PTEs) (Fe, Zn, Mn, Pb, Cr, and Ni) in water resources from the Umunya area, Nigeria. Physicochemical measurements followed standard methods. Results of the MHMI, SPI, and EWQI revealed that about 60% of the water samples had low pollution and were considered suitable for human consumption, while 40% were unsuitable. Further, cumulative non-carcinogenic health risk scores indicated that 60% of the water samples pose low-medium risks while 40% pose high risks to child and adult populations. Contrarily, results of cumulative carcinogenic health risk showed that 6.67% of the samples expose water users to low risks, whereas 93.33% expose them to high risks. Although there are agreements between the results for both adult and child populations (regarding non-carcinogenic and carcinogenic risks), it is worth highlighting that the risk scores for children were higher. Therefore, children in the study area are more vulnerable to both carcinogenic and non-carcinogenic health risks. Also, it was revealed that the risk due to ingestion was higher than that due to dermal contact. Linear regression analysis showed strong agreement between the indexical models and the cumulative health risks. While artificial neural networks and multiple linear regression models accurately predicted the water quality indices, hierarchical dendrograms efficiently classed the water samples into various spatiotemporal water quality groups

The impact of hydrogeomorphological characteristics on gullying processes in erosion-prone geological units in parts of southeast Nigeria

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

Performances of MLR, RBF-NN, and MLP-NN in the evaluation and prediction of water resources quality for irrigation purposes under two modeling scenarios

One of the pivotal decision-making tools for sustainable management of water resources for various uses is accurate prediction of water quality. In the present paper, multiple linear regression (MLR), radial basis function neural network (RBF-NN), and multilayer perceptron neural network (MLP-NN) models were developed for the monitoring and management of irrigation water quality (IWQ) in Ojoto area, southeastern Nigeria. This paper is the first to integrate and simultaneously implement these predictive methods for the modeling of seven IWQ indices. Moreover, two modeling scenarios were considered. Scenario 1 represents predictions that utilized the specific physicochemical parameters for calculating the IWQ indices as input variables while Scenario 2 represents predictions that utilized pH, EC, Na+, K+, Mg2+, Ca2+, Cl-, SO42-, and HCO3- as inputs. In terms of salinity hazard, most of the water resources are unsuitable/poor for irrigation. However, in terms of carbonate and bicarbonate impact and magnesium hazard, majority of the samples have good and excellent IWQ. Seven agglomerative Q-mode dendrograms spatiotemporally classified the water resources based on the IWQ indices. Model validation metrics showed that the MLR, RBF-NN, and MLP-NN models developed in the two scenarios performed well in both scenarios, with minor variations

Extent of anthropogenic influence on groundwater quality and human health-related risks: an integrated assessment based on selected physicochemical characteristics

The majority of people living on earth rely on groundwater as their primary supply of water for daily needs. However, human activities continuously threaten this natural resource. In an attempt to unravel the extent of the impact of human-related activities on groundwater physicochemical characteristics in Nnewi and Awka urban clusters (Nigeria), several techniques were integrated in this study. Groundwater samples were warm and acidic in nature. Concentrations of SO42-, NO3-, PO43-, Cl-, HCO3-, Ca2+, Mg2+, Na+ and K+ were within set benchmarks. The water nutrient pollution index (ranging from 0.060 to 0.745), nitrate pollution index (varying between −0.999 and −0.790) and water pollution index (ranging from 0.057 to 0.630) estimated the extent of anthropogenic contamination and showed low anthropogenic impact on the groundwater physicochemical characteristics. The health risks due to the ingestion and skin absorption of the nitrate-contaminated water computed for six age groups (6–12 months, 5–10 years, 10–15 years, 15–20 years, 20–60 years and >60 years) showed health risk values that were < 1, implying low chronic health risks to humans. The cumulative total health hazard index ranged between 0.006 and 0.787 with a mean value of 0.167. Chemometric analyses and geochemical plots revealed the relationships between the variables and contamination sources. Chadha’s plot showed that 55% of the samples were Ca2+-Mg2+-Cl- waters, predominating over Na+-Cl- and Ca2+-Mg2+-HCO3- waters. Bivariate and multivariate geochemical plots also indicated low anthropogenic impact. Furthermore, principal component analysis and R-type hierarchical clustering confirmed that the groundwater chemistry and quality were mostly influenced by geogenic processes than human-related acts. Conclusively, the extent of anthropogenic influence on groundwater physicochemical characteristics is low. These findings would be useful in future monitoring of groundwater in both urban clusters

Influence of natural and anthropogenic factors on the hydrogeology and hydrogeochemistry of Wadi Itwad Aquifer, Saudi Arabia: Assessment using multivariate statistics and PMWIN simulation

The quantity and quality of the aquifers have been depleted by human activities such as industrialization, the use of fertilizers, excessive pumping, and the discharge of domestic wastewater. The government of Saudi Arabia (SA) built three dams in the Wadi Itwad so that Abha city could get 15,000 m3/d of water. Ten groundwater samples have been collected from ten wells (Well 1 – Well 10) located in Wadi Itwad. The samples were analyzed for total dissolved solids (TDS), electrical conductivity (EC), pH, turbidity, temperature, chloride (Cl-), potassium (K), sulphate (SO42-), nitrate (NO3–), nitrite (NO2–), fluoride (F-), ammonia (NH4), radium (Ra)-226, 228, and 234, total uranium (TU), and total faecal coliforms to evaluate the aquifer quality and quantity and to preserve it by isolating it during dry periods. Geographic Information System (GIS)–Inverse Distance Weighting (IDW) contour maps were utilized to collect and display the aquifer's hydrogeological parameters. The southeast of the downstream area shows the highest, whereas the lowest drawdown was in the northeastern and southwest parts of the downstream area. The TDS concentration was consistently within a narrow range of 573 to 606 ppm, and the anomalies in the SO42- and NO3– concentrations were consistent with and representative of runoff from agricultural areas. The low levels of NO2–, F-, and NH4 indicated negligible pollution. The concentration of radioactive elements was below the maximum contaminant level. Different hydrogeochemical processes within the aquifer system were distinguished using multivariate statistical analyses, including correlation analysis (CA), principal component analysis (PCA), hierarchical cluster analysis (HCA), and one-way analysis of variance (ANOVA). The Processing Modflow Windows (PMWIN) groundwater modeling explains that the abstraction rate needs to be lowered during the first few days of pumping and then raised again afterwards. This could aid in decreasing withdrawals and enhancing aquifer hydrogeological properties

Occurrences, sources and health hazard estimation of potentially toxic elements in the groundwater of Garhwal Himalaya, India

Abstract 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

Prediction of Sodium Hazard of Irrigation Purpose using Artificial Neural Network Modelling

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