Hydrogeochemical Studies to Assess the Suitability of Groundwater for Drinking and Irrigation Purposes: The Upper East Region of Ghana Case Study

Abstract

Groundwater is increasingly being used to help meet the Sustainable Development Goals (SDGs) 2 and 6 in many parts of the world, including Ghana. Against this background, hydrogeochemical and multivariate statistical studies were conducted to determine the physicochemical characteristics and suitability of groundwater in some agrarian communities in the Upper East Region of Ghana for drinking and irrigational farming. Additional analyses were also performed to identify potential health risks associated with the groundwater use and to better understand the hydrogeochemical processes controlling groundwater evolution for its effective management. The results showed that the groundwater is typically fresh; moderate to very hard in character; undersaturated with calcite, dolomite, halite, and gypsum; and supersaturated with quartz and amorphous silica. The physicochemical characteristics of the groundwater are controlled by both anthropogenic and natural activities/processes, such as fertilizer application, irrigation return flows, rock weathering, and forward/reverse cation exchange. The total dissolved solids (TDS) (165–524 mg/L), electrical conductivity (EC) (275–873 μS/cm), sodium percentage (Na%; 9.05–17.74%), magnesium ratios (MR) (29.25–53.3%), permeability index (PI) (36.6–74.6%), and sodium adsorption ratio (SAR) (0.20–0.51) point to the possibility of using the groundwater for irrigation, however, with some salinity control. The water quality and health risk analysis also revealed that the groundwater can be used for drinking; however, the high concentrations of fluoride, which can cause noncarcinogenic health issues such as dental and skeletal fluorosis in both adults and children, must be reduced to the WHO required level of 1.5 mg/L.

1. Introduction

In 2015, the United Nations adopted seventeen (17) Sustainable Development Goals (SDGs) to ensure a sustainable future for all [1]. Many of these goals, particularly SDGs 2 and 6, depend heavily on water resources [1,2,3]. The overarching goal of SDG 2, which is “Zero Hunger”, aims to end hunger, achieve food security, improve nutrition, and support sustainable agriculture, while SDG 6, inter alia, aims to provide everyone with access to affordable and safe drinking water [4]. Although significant progress is being made to accomplish these goals on a global scale, the implementation of these goals is rather slow in many countries in sub-Saharan Africa (SSA) [5].

Access to safe drinking water, which is a fundamental human right and essential to everyone’s health, remains a major issue in SSA and, thus, in Ghana [6,7]. Similarly, agriculture which is heavily reliant on rainfall in many parts of SSA is steadily declining. For example, the agricultural sector that, in the 1980s, contributed more than 40% to GDP in Ghana accounted for only 20% of the GDP in 2020 [8,9]. These issues have been largely attributed to: (i) climate change that has either resulted in the depletion of surface water bodies that provide water for drinking and irrigation or made rainfall patterns and intensities more unpredictable and (ii) anthropopression that has led to contamination of surface water bodies, making them unsafe for human use [10,11,12,13].

The use of groundwater to complement or as an alternative to rainfall or surface water to help meet, particularly, SDGs 2 and 6 is increasing globally but, more especially, in the arid and semi-arid areas [13,14,15]. In India, for instance, groundwater is playing an enormous role in agricultural development and transformation and improving food security [16]. According to Giordano [17], groundwater supplies water for about one million hectares of individual or community irrigation projects in many parts of SSA. Although many researchers, e.g., [6,18,19], have indicated that there is sufficient groundwater in SSA that can be used to significantly improve agricultural production, income, and food security, as well as meet the growing drinking water demand, the groundwater must meet certain standards in terms of quality (i.e., its physical–chemical and biological characteristics) with respect to its suitability for a particular purpose [6,13]. For instance, Shah and Mistry [20] noted that the suitability of groundwater for irrigation depends on the nature of the mineral elements in the water. Meireles et al. [21] also indicated that groundwater with high electrical conductivity (EC) and total dissolved solids (TDS) is not suitable for agriculture, as it can affect plant growth and soil productivity. Continuous use of irrigation water that is highly saline, sodic, and has excess of Mg²⁺ can also render soils unsuitable for crop production [22,23,24].

Hydrogeochemical studies are vital for the supply of adequate groundwater of suitable quality and the sustainable management of groundwater resources. Hydrogeochemical studies allow the determination of the origin of groundwater chemical constituents, processes controlling groundwater chemistry, quality status, and appropriate usability [24,25,26]. Numerous hydrogeochemical studies have shown that, during the groundwater flow from recharge to discharge areas, groundwater chemistry and quality can be influenced by a variety of natural (geogenic) processes/activities, including the weathering of aquifer material or host rock, leaching from soil, and runoff caused by hydrological factors [27,28]. The magnitude of these processes has been shown to depend on a number of interconnected factors, such as geology, climate, soil characteristics, topography, groundwater residence time, pH, and ambient temperature [26,29,30]. In addition to the above natural processes, emissions/effluents from anthropogenic sources such as landfills, farmlands, mining and chemical industries can also significantly impact the quality of groundwater [26,30,31].

A variety of methods have been employed to identify and understand the hydrogeochemical processes influencing the physicochemical properties of groundwater. Yidana et al. [32] applied multivariate statistical methods and the geographic information system (GIS) to evaluate the major factors affecting groundwater chemistry in some parts of the Voltaian aquifers in the northern region of Ghana. Helstrup et al. [33] used Q-mode multivariate techniques and mass balance methods to study the hydrochemistry of groundwater from some sedimentary aquifers in Southern Ghana and Togo. They concluded that the groundwater hydrochemistry was controlled predominantly by carbonate equilibria, silicate mineral weathering, seawater intrusion, and ion exchange mechanisms. Zango et al. [34] also employed multivariate statistical techniques, such as principal component analysis (PCA) and R-mode factor analysis, to comprehend the hydrochemical controls on groundwater. The geochemical modeling code PHREEQC has also been used to perform speciation and compute saturation indices to understand the geochemical processes taking place in an aquifer [26,35,36]. Bivariate plots of major ions, plots of hydrochemical data on Piper, Gibbs, and Korjinski diagrams, as well as the determination of chloralkaline indices, have also been frequently used to delineate the main geochemical processes responsible for the evolution of groundwater chemistry [35,36,37,38,39].

The quality of groundwater vis-à-vis its suitability for irrigation has been widely evaluated in many hydrogeochemical studies using indicators such as percentage sodium (%Na), magnesium ratio (MR), sodium adsorption ratio (SAR), EC, and permeability index (PI). Others such as the Wilcox and United States Salinity Laboratory Staff diagrams have also been employed to provide additional information on the suitability of groundwater for agricultural irrigation [40,41,42,43,44]. Similarly, the quality of groundwater for drinking purposes has commonly been ascertained with the water quality index (WQI), which is sometimes coupled with graphical methods such as GIS [45,46]. To complement or buttress the information from the hydrogeochemical studies and water quality assessment, a health risk assessment (HRA) has also been performed to evaluate the potential harm associated with water contaminants [47,48].

The Upper East Region of Ghana is well-known for producing food crops that aid in food security and nutrition while also contributing significantly to Ghana’s GDP. However, climate change and human activities have had a significant impact on the region’s rainfall patterns and surface water bodies. As a result, the reliance on groundwater for drinking and irrigation has increased dramatically. Currently, studies to ascertain the quality and identify processes/activities that influence the chemistry of groundwater resources in the region are few and limited to only a few areas. For instance, Okofo et al. [36] characterized groundwater in the ‘Tamnean ‘Plutonic Suite aquifers of the region using hydrogeochemical and multivariate statistics. They noted that the dissolution of silicate mineral and cation exchange coupled with the leaching of domestic solid waste and nitrogen-based fertilizers predominantly controlled the groundwater chemistry. Craig et al. [35] also characterized the hydrogeology, geochemistry, and groundwater chemistry of the Namoo community in the Upper East Region to better understand the distribution of groundwater fluoride and to identify the conditions that may influence its concentration. The findings of [49] also suggested that some parts of the region may be experiencing fluoride contamination from geogenic sources. New boreholes were recently drilled in some agrarian communities in this region to supply water for both domestic and agricultural purposes. In these areas, studies providing information on the hydrochemistry of the groundwater are sparse. Thus, multivariate statistical and hydrogeochemical methods were integrated in the present study to: (1) determine the physicochemical characteristics of the groundwater, (2) assess the suitability of the groundwater for drinking and irrigation, (3) identify the sources of the ionic constituents and the major controls of groundwater composition/characteristics, and (4) evaluate the health risk associated with the groundwater use for drinking. This research will improve our understanding of groundwater resources in the region and aid in the identification of management options for the sustainable use of groundwater for various purposes, thus helping to achieve SDGs 2 and 6.

2. Materials and Methods

2.1. Study Area

2.1.1. Location

The study area is located in Bongo District in the Upper East Region of Ghana and is bounded by longitudes 0.48° W and 0.54° W and latitudes 10.52° N and 10.58° N (Figure 1A). The area falls within Ghana’s semi-arid climate region and the Guinea savannah agro-ecological zone. The study area experiences two seasons: the wet season (April–October) and the dry season (November–March). The dry season is generally cold and laced with the North East trade winds (harmattan weather). The mean shade temperatures range from 12 °C at night to 40 °C in the day during the hot season. The area has a unimodal precipitation regime that starts in April/May and ends in October/November. The annual rainfall in the region varies between 600 mm and 1400 mm, with an annual mean of 935 mm. The majority of the precipitation occurs between the months of July and September [14,25]. The topography of the study area is generally flat and hilly in some parts [50]. Until recently, residents in the study area relied majorly on rainfall and surface water bodies for drinking and agricultural activities. Major food crops grown in the area include: cereals (e.g., sorghum, millet, maize, and rice); legumes (e.g., groundnuts, cowpea, soybeans, and Bambara beans); fibers (e.g., kenaf, cotton, and kapok); roots and tubers (e.g., sweet potato and frafra potato); and vegetables (e.g., okra, peppers, and leafy vegetables). Agrochemicals are commonly used to improve soil fertility and crop productivity in the study area [51,52].

2.1.2. Geology and Hydrogeology

The Bongo District is underlain by rocks of the Birimian Supergroup, with Tarkwaian rocks and granitoids of the Eburnean and Tamnean Plutonic Suites intruding (Figure 1A) [53]. The Birimian Formation is composed of two major lithostratigraphic units, i.e., the Birimian Metavolcanics and the Birimian Metasediments. The majority of the rocks in this formation are argillaceous and have metamorphosed into hornblende, actinolite schists, calcareous schists, and amphibolites in the intervening period [53]. The Tarkwaian Group consists primarily of sandstones and conglomerates, whereas the rocks forming the Tamnean Plutonic Suite comprise hornblende–biotite granitoids, alkali feldspar granite, minor quartz diorite, and tonalite [54,55]. The study area is, however, underlain primarily by the Eburnean Plutonic Suite, which mainly contains K-feldspar-rich granitoids (Bongo granite) and monzonite. The latter is composed primarily of K-feldspars and Na-plagioclase with traces of quartz and ferromagnesian minerals (e.g., hornblende, biotite, and pyroxene) [54]. The granitoids are of considerable importance, as they constitute the predominant rock types in the study area.

The northern regions of Ghana are located within Africa’s crystalline basement aquifers, which are generally confined in character. Drilling and lithological data were not available for this study; however, Wright [56] noted that the basement aquifers of Africa consist of two main components. The first component is weathered and comprises a homogeneous cover, ranging from clay to clayey sand with characteristically high porosity and low permeability, thus acting predominantly as an impermeable layer. Martin [57] reported that the clay content of this component decreases while the sand fraction increases with the depth until the second component (consisting mainly of fractured bedrocks) is reached. The bedrocks of the second component vary in thickness and are inherently impermeable; however, due to fracturing and weathering, they have developed secondary permeability and porosity, which largely control groundwater occurrence in the component. Groundwater is mostly tapped from this component with borehole depths generally ranging from 35 m to 55 m [58]. According to [54], the weathered layer can be as thick as 100 m. Groundwater recharge occurs principally through the direct infiltration of precipitation and, to a lesser extent, from influent streams and rivers [54]. Transmissivity has been reported to range from 0.3 m²/day to 114 m²/day, with an average of 6.6 m²/day in granitoids terrains [58]. The recharge rates estimated theoretically from the analysis of recharge, lithology, and total annual rainfall for areas in Northern Ghana range from 3.7 to 5% of the annual rainfall [59]. Generally, the groundwater level in the area varies from 2 to 16 m below ground level (mbgl) [34] and flows from the north to south (Figure 1B). Groundwater in the region is typically tapped through hand-dug wells or by boreholes that are fitted with hand pumps in the region.

2.2. Sampling and Analytical Procedures

Groundwater samples were collected from 10 boreholes (BH) in four communities, namely: Bongo, Zoko, Sambolugu, and Yorogo in September 2021 and analyzed according to the standard protocols [60]. Before sampling, the wells were flushed by pumping groundwater until the EC and pH values were stable. Samples were collected in clearly labeled plastic bottles and transported in a cool box with ice to the CSIR-WRI laboratories and analyzed for their physicochemical parameters. EC and pH were measured using Hach HQ440d Multi-Parameter and Oakton PC 450 pH meters, respectively. Major ions, including sodium (Na⁺) and potassium (K⁺), were determined by flame photometry, while calcium (Ca²⁺), magnesium (Mg²⁺), total hardness (TH), and bicarbonate (HCO₃⁻) were determined by titrimetric methods. TDS was measured using an Oakton PC 450 multipurpose conductivity meter, whereas nitrate (NO₃⁻), chloride (Cl⁻), sulphate (SO₄²⁻), phosphate (PO₄³⁻), and fluoride (F⁻) were determined by hydrazine reduction, argentometric, turbidimetric, stannous chloride, and SPADNS methods, respectively. Aqueous silica (SiO₂) was determined using a UV–visible spectrophotometer. The charge balance error (CBE) was computed using Equation (1) (concentrations of the ions are in met/L) [39] to ascertain the accuracy of the groundwater dataset. The CBE values obtained were within ±5% which is acceptable [26].

$$\mathrm{CBE} =\frac{\sum \mathrm{Cations} -\sum \mathrm{Anions}}{\sum \mathrm{Cations} +\sum \mathrm{Anions}}\times 100\%$$

(1)

2.3. Drinking Water Quality Assessment

The quality of the groundwater for drinking purpose was assessed using the water quality index (WQI) [46]. Each groundwater parameter was given a numerical weight (wi) from 3 to 5 based on the magnitude of its impact on drinking water quality. This was followed by estimating each parameter’s relative weight (W_r) using Equation (2). The quality rating (q_i) was performed using Equation (3), while Equation 4 was used to determine the sub-index, S_ID for each parameter. The WQI was then calculated using Equation (5).

$${\mathrm{W}}_r=\frac{{\mathrm{w}}_{\mathrm{i}}}{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{w}}_{\mathrm{i}}}$$

(2)

$${\mathrm{q}}_{\mathrm{i}}=\left(\frac{{\mathrm{C}}_{\mathrm{i}}}{{\mathrm{S}}_{\mathrm{i}}}\right)\times 100$$

(3)

$${\mathrm{S}}_{\mathrm{ID}}={\mathrm{W}}_r\times { \mathrm{q}}_{\mathrm{i}}$$

(4)

$$\mathrm{WQI}=\sum _{i=1}^n{\mathrm{S}}_{\mathrm{ID}}$$

(5)

where: W_r is the relative weight; w_i is the weight of each parameter; q_i is the quality rating; C_i is the value of the chemical parameter in the groundwater sample (mg/L); S_i is the standard value for the chemical parameter (mg/L); S_ID is the sub-index; WQI is the water quality index, and n is the number of chemical parameters analyzed.

Table 1. Numerical weights, relative weights, and standard values of the parameters used to estimate the water quality index (WQI).

Parameter	Unit	Assigned Weight (wi)	Relative Weight (Wr)	Drinking Water Guideline Value (mg/L) [61]
pH	pH units	5	0.088	7.5
TDS	mg/L	5	0.088	1000
Na+	mg/L	4	0.070	200
K+	mg/L	3	0.053	30
Ca2+	mg/L	5	0.088	200
Mg2+	mg/L	4	0.070	150
Cl−	mg/L	5	0.088	250
SO42−	mg/L	4	0.070	250
PO43−	mg/L	3	0.053	0.7
NO3−	mg/L	4	0.070	10
TH	mg/L	5	0.088	200
HCO3−	mg/L	5	0.088	150
F−	mg/L	5	0.088	1.5

shows the weight assigned to each chemical parameter, their standard values and relative weights.

2.4. Irrigation Water Quality Assessment

The suitability of the groundwater for irrigation was evaluated based on the TDS, EC, percentage sodium ion (Na⁺ %) (Equation (6)), magnesium ratio (MR) (Equation (7)), SAR (Equation (8)), and permeability index (PI) (Equation (9)), as well as the Wilcox and United States Salinity Laboratory Staff diagrams [13,20,40,41,42,44].

$$\mathrm{Na}\%=\frac{{\mathrm{Na}}^{+}+{ \mathrm{K}}^{+}}{{\mathrm{Na}}^{+}+{ \mathrm{K}}^{+}+{\mathrm{Ca}}^{2+}+{ \mathrm{Mg}}^{2+}}\times 100$$

(6)

$$\mathrm{MR}=\frac{{\mathrm{Mg}}^{2+}}{{\mathrm{Mg}}^{2+}+{ \mathrm{Ca}}^{2+}}\times 100$$

(7)

$$\mathrm{SAR}=\frac{{\mathrm{Na}}^{+}}{\sqrt{\frac{{\mathrm{Ca}}^{2+}+{\mathrm{Mg}}^{2+}}{2}}}$$

(8)

$$\mathrm{PI}=\frac{\left({\mathrm{Na}}^{+}+\sqrt{{\mathrm{HCO}}_3}\right)}{{\mathrm{Na}}^{+}+{ \mathrm{Ca}}^{2+}+{ \mathrm{Mg}}^{2+}}\times 100$$

(9)

2.5. Identification of the Hydrogeochemical Processes

The Piper diagram [37], Korjinski and Gibbs diagrams [38], plots and ratios of major cations and anions [62], and the saturation indices of major minerals [27] were employed to understand the hydrogeochemical processes controlling the chemistry of the groundwater.

2.6. Multivariate Statistical Analyses

Correlation and principal component analyses were also performed using version 4.03 of the Paleontological Statistics (PAST) Software Package [63] to study the relationships between the groundwater quality parameters and to deduce the sources of the ionic constituents of the groundwater.

2.7. Health Risk Assessment

Due to the findings of [49], an HRA was carried out to determine the probability of occurrence of noncarcinogenic health effects of fluoride to adults and children. Ingestion (drinking) was identified as the principal route for fluoride exposure. The chronic daily intake (CDI) of F⁻ via the ingestion route was determined using Equation (10) [64].

$${\mathrm{CDI}}_{\mathrm{ing}}=\frac{{\mathrm{C}}_{\mathrm{w}}\times \mathrm{IR} \times \mathrm{EF} \times \mathrm{ED}}{\mathrm{BW} \times \mathrm{AT}}$$

(10)

All the parameters in Equation (10) as well as the reference values are explained in

Table 2. Parameters used to calculate the chronic daily intake (CDI) (mg/kg/day) and the hazard quotient (HQ) of fluoride for adults and children.

Parameter	Interpretation	Units	Values
			Adult	Children
Cw	Contaminant concentration in groundwater	mg/L	Observed concentration	Observed concentration
IRwater	Ingestion rate	L/day	2.2	1.8
EF	Exposure frequency	Day/yr	365	365
ED	Exposure duration	yr	30	6
BW	Body weight	kg	70	15
AT	Average time (noncarcinogenic)	day	10,950	2190
RfD (F−)	Reference dose of fluoride	(mg/kg/day)	6.0 × 10−2	6.0 × 10−2

. To ascertain whether or not fluoride exposure may present noncarcinogenic health effects, the hazard quotient (HQ) of F⁻ was determined using Equation (11) [64]. HQ represents the systemic toxicity potentially posed by a single element within a single route of exposure.

$$\mathrm{HQ}=\frac{{\mathrm{CDI}}_{\mathrm{ingestion}}}{\mathrm{RfD}}$$

(11)

where: HQ_(ingestion) is the hazard quotient for the ingestion route; RfD (mg/kg/day) is the reference dose. Noncarcinogenic effect with respect to fluoride may not exist if the estimated HQ is less than 1 whereas the population may be exposed to the noncarcinogenic effects of fluoride if HQ >1 is obtained [64].

3. Results and Discussion

3.1. Physicochemical Characteristics of Groundwater

A statistical overview of the physicochemical characteristics of the groundwater is shown in

Table 3. Summary statistics of the groundwater physicochemical properties.

Statistics /Parameter	pH	EC (μS/cm)	TDS (mg/L)	Alk (mg/L)	Tot. H (mg/L)	Ca2+ (mg/L)	Mg+ (mg/L)	Na+ (mg/L)	K+ (mg/L)	Cl− (mg/L)	HCO3− (mg/L)	NO3-N (mg/L)	PO43− (mg/L)	SO42 (mg/L)	F− (mg/L)	SiO2 (mg/L)
N	10.0	10.0	10.0	10.0	10.0	10.0	10.0	10.0	10.0	10.0	10.0	10.0	10.0	10.0	10.0	10.0
Min	6.7	275.0	165.0	90.6	107.8	22.8	8.1	4.7	1.1	4.8	110.5	0.0	0.1	1.0	1.9	114.7
Max	7.2	873.0	524.0	200.0	354.4	85.5	34.6	22.0	2.5	113.0	244.0	0.4	0.3	10.5	6.5	152.9
Sum	69.3	4410.0	2646.8	1331.4	1712.6	389.6	180.5	105.3	16.5	319.4	1624.0	1.7	1.8	67.3	35.4	1411
Mean	6.9	441.0	264.7	133.1	171.3	39.0	18.1	10.5	1.7	31.9	162.4	0.2	0.2	6.7	3.5	141.1
Stand. dev	0.1	178.3	107.0	32.5	75.4	18.0	8.1	5.2	0.5	32.6	39.7	0.1	0.1	3.3	1.9	12.6
Median	6.9	386.0	231.8	138.0	145.6	34.9	14.6	9.4	1.6	20.8	168.4	0.1	0.2	6.8	2.4	143.4
WHO (2017)	6.5–8.5	-	1000	-	-	200	150	200	30	250	150	50	0.7	250	1.5	-

. The distribution and probability density of the hydrochemical data were also presented graphically using the violin plot (Figure 2), which is a combination of the kernel density and box plots. The interior of the violin plot is a box plot, which shows the maximum value, mean, standard deviation, median, upper quartile, and lower quartile. The exterior of the violin plot, on the other hand, is a kernel density plot, which shows how the data is distributed. The pH of the water samples ranged from 6.7 to 7.2, with an average value of 6.9, indicating that the groundwater in the study area is neutral in nature. The EC values varied from 275 to 873 µS/cm, indicating low enrichment of salts [65]. The corresponding TDS values were also low (165 to 524 mg/L), indicating limited contact between the groundwater and the host rock. Based on the TDS values, the groundwater in the study area is classified as fresh (TDS < 1000 mg/L) [29]. The TH values varied from 107.8 to 354.4 mg/L (average value of 133.14 mg/L), indicating that the groundwater is moderately to very hard in character [65]. Alkalinity values also ranged from 90.60 to 200 mg/L. Alkalinity refers to the ability of the groundwater to neutralize acidity and is determined by the bicarbonate (HCO₃⁻) and carbonate (CO₃²⁻) concentrations [65]. Na⁺ and K⁺ concentrations ranged from 4.7 to 22.0 mg/L, with a mean value of 10.5 mg/L, and from 1.1 to 2.5 mg/L, with an average of 1.7 mg/L, respectively. Mg²⁺ and Ca²⁺ concentrations, on the other hand, respectively, varied between 8.1 and 34.6 mg/L, with a mean value of 18.1 mg/L, and between 22.8 and 85.5 mg/L, with a mean of 39.0 mg/L. Concentrations of Cl⁻ varied from 4.8 to 113.0 mg/L (average value of 31.9 mg/L), while PO₄³⁻ and NO₃⁻ ranged between 0.1 and 0.3 mg/L and between 0.0 and 0.4 mg/L, respectively. The concentrations of F⁻ and SO₄²⁻ varied, respectively, from 1.9 to 6.5 mg/L (mean value of 3.5 mg/L) and from 1.0 to 10.5 mg/L (mean value of 6.7 mg/L). All the samples had very high HCO₃⁻ concentrations, which ranged from 110.5 to 244.0 mg/L. Except for fluoride concentrations which exceeded the allowable level of 1.5 mg/L, the values of all the other physicochemical parameters were below or within the WHO tolerable limit or range [61]. Although fluoride is an essential element for maintaining the normal development of teeth and bones, high levels in groundwater can cause health problems, such as dental fluorosis, osteoporosis, arthritis, and thyroid in both adults and children [66]. Overall, the abundance of the major cations was in the order: Ca²⁺ > Mg²⁺ > Na⁺ > K⁺, while the anion abundance occurred in the order: HCO₃⁻ > Cl⁻ > SO₄²⁻ > F⁻ > NO₃⁻ = PO₄³⁻.

3.2. Hydrochemical Facies of Groundwater

The concentrations of the major cations and anions in the samples were plotted on a Piper trilinear diagram to determine the facies of the groundwater. As shown in Figure 3, all the samples plotted in the Ca-Mg-HCO₃ domain, inferring that the groundwater is characteristically the Ca-Mg-HCO₃ type that is dominated by alkaline earth metals (e.g., Ca²⁺, and Mg²⁺) and weak acid anions (e.g., HCO₃). Hounslow [39] noted that HCO₃⁻, Ca²⁺ and Mg²⁺ ions are typically dominant in groundwater with pH varying between 6.5 and 7.8. According to [67], the Ca-Mg-HCO₃ water type has a transitory hardness and is typical of freshwaters formed by the incongruent weathering of silicate or dissolution of carbonate minerals. Adams et al. [68] also noted that the Ca-Mg-HCO₃ water type is widespread in recharge zones, where the waters are in the early stages of geochemical evolution and have limited interaction with the host rock. This indicates that the studied aquifer is characterized by freshly recharged groundwater.

3.3. Hydrogeochemical Processes

The Gibbs diagrams were plotted to determine the contribution of natural processes, including precipitation, rock weathering (rock–water interaction), and evaporation, to groundwater chemistry in the study area [69]. As shown in Figure 4, all the samples plotted in the rock-weathering domain, indicating that the major ions in the groundwater largely derived from weathering of the host rock as the groundwater moved along its path. The plot of Na/Cl versus EC (Figure 5) was further used to verify the effect of evaporation on the chemistry of the groundwater. Jankowski and Acworth [70] noted that, if evaporation is dominant, the Na/Cl ratio would remain the same. Hence, the plot of Na/Cl versus EC would give a horizontal line. However, as shown in Figure 5, the ratio of Na/Cl decreased as EC increased, indicating that evaporation is not a major process influencing groundwater chemistry in the study area.

During the flow of groundwater through the aquifer matrix, a number of hydrogeochemical processes including weathering, dissolution or precipitation of minerals, ion exchange (forward and reverse), and oxidation and reduction can occur. The hydrochemical data were further analyzed to identify/verify the hydrogeochemical processes influencing the groundwater chemistry in the study area. According to Rogers [71], if silicate weathering is a major process releasing Ca²⁺, Mg²+, Na⁺, and K⁺ into the groundwater, HCO₃⁻ would be the most abundant anion. Hounslow [39] also noted that TDS levels would generally be less than 500 mg/L in waters whose chemical composition is mostly impacted by silicate weathering. Consistent with [39,71], HCO₃⁻ was the dominant anion in the tested samples, and TDS was less than 500 mg/L in all but one sample, indicating that silicate weathering is a major process influencing the chemistry of the groundwater. Hounslow [39] further noted that carbonate weathering would be the major source of HCO₃⁻ if the HCO₃-/SiO₂ molar ratio is greater than ten (i.e., HCO₃⁻ >> SiO₂), whereas a ratio less than five would be obtained if silicate weathering predominates. The HCO₃⁻/SiO₂ ratios computed for the water samples varied from 0.81 to 1.51, indicating that weathering of silicate minerals (as generally shown in Equation (12)) is the predominant process releasing Ca²⁺, Mg²⁺, Na⁺, K⁺, and HCO₃⁻ into the groundwater in the study area.

$$({\mathrm{Na}}^{+},{ \mathrm{K}}^{+},{ \mathrm{Ca}}^{2+},{ \mathrm{Mg}}^{2+}) \mathrm{silicate}+2{\mathrm{H}}_2{\mathrm{CO}}_3\to {\mathrm{Ca}}^{2+}+{\mathrm{Mg}}^{2+}+{ \mathrm{K}}^{+}+2{\mathrm{Na}}^{+}+{\mathrm{HCO}}_3^{-}+{ \mathrm{H}}_4{\mathrm{SiO}}_4+\mathrm{solid} \mathrm{product} \left(\mathrm{e}.\mathrm{g}., \mathrm{kaolinite}\right)$$

(12)

Graphs of Na⁺ versus Cl⁻ and (Ca²⁺ + Mg²⁺) versus (SO₄²⁻ + HCO₃⁻) were also plotted to allow further understanding of the processes controlling the concentrations of Na⁺, Cl⁻, Ca²⁺, Mg²⁺, SO₄²⁻ and HCO₃⁻ in the groundwater. According to Hounslow [39], halite dissolution is the source of Na⁺ if the samples fall on the 1:1 line in the graph of Na⁺ versus Cl⁻. On the other hand, if the samples fall above the 1:1 line it indicates seawater intrusion and/or wastewater mixing with the groundwater, whereas samples below the 1:1 line reflect weathering of silicate minerals rich in Na⁺ such as albite or the effects of anthropogenic activities such as seepage of wastewater. Ion exchange (forward) between Na+, Mg²⁺ and Ca²⁺ will also shift the points to the right whereas reverse cation exchange will shift the points to the left due to excess Cl⁻ over Na⁺. As shown in Figure 6A, the majority (80%) of the samples plotted above the 1:1 (i.e., Na/Cl ratio < 1) while the rest (20%) plotted below the 1:1 (i.e., Na/Cl ratio > 1). Since there is no evidence of groundwater interaction with connate seawater in the study area, the observed Na/Cl < 1 could be attributed to either Cl enrichment from anthropogenic sources such as irrigation return flows or domestic waste disposal, or it could be due to Na⁺ depletion as a result of reverse cation exchange as shown in Equation (13) below; where X represents the aquifer matrix.

$$\frac{1}{2}\mathrm{Ca}\left(\mathrm{Mg}\right)-{\mathrm{X}}_2+{ \mathrm{Na}}^{+}\to \mathrm{Na}-\mathrm{X}+\frac{1}{2}{\mathrm{Ca}}^{2+}({\mathrm{Mg}}^{2+})$$

(13)

Rajmohan and Elango [72] also indicated that when the data points fall on the 1:1 line in the graph of (Ca²⁺ + Mg²⁺) versus (SO₄^2- + HCO₃⁻), it indicates that the concentrations of Ca²⁺, Mg²⁺, SO₄²⁻ and HCO₃⁻ in the groundwater are influenced by the dissolution of calcite, dolomite, and/or gypsum. On the other hand, when the samples fall above the equiline it indicates silicate weathering and/or ion exchange, whereas plots below the equiline indicate carbonate dissolution and/or reverse cation exchange. As shown in Figure 6B, two of the samples representing 20% plotted above the 1:1 line, indicating silicate weathering and/or normal ion exchange, whereas the rest (80%) plotted around and below the equiline. This might be due to reverse cation exchange [72] since carbonate and sulphate minerals are practically nonexistent in the area [35,55].

To verify the occurrence of ion exchange in the aquifer, a graph of [Na⁺ − Cl⁻] versus [(Ca²⁺ + Mg²⁺) − (HCO₃⁻ + SO₄²⁻)] was plotted. According to Jalali [73], if an ion exchange is taking place, a very strong linear correlation between the parameters with a slope of −1 will be obtained in the graph of [Na⁺ − Cl⁻] versus [(Ca²⁺ + Mg²⁺) − (HCO₃⁻ + SO₄²⁻)]; otherwise, all the points would cluster at the origin. As shown in Figure 7, all the samples plotted on or around the straight line with a slope of −1.39 and a very strong correlation, R² = 0.98, indicating the occurrence of ion exchange between Na⁺, Mg²⁺, Ca²⁺, and K⁺ in the study area.

The Schoeller indices, CAI-I (Equation (14)) and CAI-II (Equation (15)) (with all ions expressed in meq/L) were further used to indicate the type of ion exchange mechanism occurring in the aquifer [74]. Both indices would be negative if normal (forward) cation-exchange activities were prevalent, and positive if reverse cation-exchange processes were present. The CAI-I values varied from −2.05 to 0.68, whereas CAI-II ranged from -0.10 to 0.52. Positive CAI-I and CAI-II values were exhibited by 80% of the samples, indicating reverse cation exchange, in which the Na⁺ and K⁺ in the groundwater are replaced by Ca²⁺ and Mg²⁺ from the aquifer matrix. Negative CAI-I and CAI-II values were obtained for the remaining 20% samples, indicating forward or normal cation exchange in which Ca²⁺ and Mg²⁺ in the groundwater are replaced by Na⁺ and K⁺ from the aquifer material.

$$\mathrm{CAI}-\mathrm{I}=\frac{\left[{\mathrm{Cl}}^{-}-\left({\mathrm{Na}}^{+}+{\mathrm{K}}^{+}\right)\right]}{{\mathrm{Cl}}^{-}}$$

(14)

$$\mathrm{CAI}-\mathrm{II}=\frac{\left[{\mathrm{Cl}}^{-}-\left({\mathrm{Na}}^{+}+{\mathrm{K}}^{+}\right)\right]}{({\mathrm{HCO}}_3^{-}+{\mathrm{SO}}_4^{2-}+{\mathrm{NO}}_3^{-}+{\mathrm{CO}}_3^{2-})}$$

(15)

As indicated earlier, the ionic constituents of the groundwater are largely due to the dissolution of primary rock minerals and ion exchange processes. The Korjinski diagram was further used to identify the minerals that are in equilibrium with the analyzed waters. The diagram was drawn assuming a temperature of 25 °C and a pressure of 1 atm. As illustrated in Figure 8, all the samples plotted in the green field, which comprises minerals including goethite [FeO(OH)], quartz (SiO₂), kaolinite [Al₂Si₂O₅(OH)₄], phlogopite [KMg₃AlSi₃O₁₀(OH)₂], and wairakite [Ca(Al₂Si₄O₁₂)·2H₂O]. This suggests the dissolution of feldspars and ferromagnesian minerals such as hornblende, biotite and pyroxene, which are common minerals in the host rock. However, kaolinite is the dominant product, indicating that the groundwater in the study area is in equilibrium with kaolinite. Weathering of silicates to kaolinite is common in the tropics and is typical of well-drained aquifer systems [26,75].

The saturation indices (SI) of various minerals, including anhydrite, calcite, dolomite, gypsum, halite, amorphous silica, and quartz were calculated with PHREEQC based on Equation (16) to help ascertain the saturation state of the groundwater samples with respect to the minerals and to investigate the thermodynamic controls on the composition of the groundwater [26].

$$\mathrm{SI}={ \log }_{10} \left(\frac{\mathrm{IAP}}{{\mathrm{K}}_{\mathrm{sp}}}\right)$$

(16)

where: SI represents the saturation index; IAP is the ion activity product, and K_sp is the solubility product at a given temperature. If the SI of a mineral phase is less than 0, it indicates that the groundwater is undersaturated with respect to that mineral, and thus its dissolution may continue. On the other hand, if the SI > 0, it implies that the groundwater is supersaturated with regard to that mineral. In that situation, the groundwater will be incapable of dissolving more of that mineral. If the SI = 0, it implies that the groundwater is in equilibrium with respect to the particular mineral [27]. As shown in

Table 4. Summary statistics of saturation indices (SI) of various minerals phases.

Mineral	Formula	Mean	Median	Standard Deviation	Minimum	Maximum
Anhydrite	CaSO4	−3.27	−3.16	0.40	−4.15	−2.79
Calcite	CaCO3	−0.73	−0.71	0.18	−0.99	−0.45
Dolomite	CaMg(CO3)2	−1.46	−1.37	0.42	−2.24	−0.93
Gypsum	CaSO4:2H2O	−3.05	−2.94	0.40	−3.93	−2.57
Halite	NaCl	−8.26	−8.34	0.55	−8.94	−7.19
Fluorite	CaF2	−0.26	−0.36	0.42	−0.81	0.26
Amorphous Silica	SiO2	0.10	0.12	0.04	0.02	0.14
Quartz	SiO2	1.36	1.37	0.05	1.26	1.40

, all the analyzed water samples were undersaturated with respect to calcite, dolomite, gypsum, halite, and anhydrite. This is mainly because of the absence of these minerals in the host rock [53,55]. On the other hand, all the samples were supersaturated with quartz and amorphous silica. The presence of these siliceous minerals in the groundwater samples is reminiscent of silicate weathering. Additionally, 40% of the samples were supersaturated with fluorite. In the Tamnean Plutonic Suite of the region, which has analogous rock composition, Okofo et al. [36] found that the groundwater was undersaturated with respect to gypsum, fluorite, halite, and anhydrite, while it was supersaturated with respect to dolomite, indicating the spatial variation in the hydrogeochemical characteristics of the groundwater in the region.

3.4. Multivariate Statistical

Figure 9 presents the Pearson’s correlation matrix showing the relationships between the examined groundwater physicochemical parameters. The pH correlated negatively with all the parameters except PO₄³⁻, NO₃⁻, and F⁻, for which the correlation was weakly positive. A positive correlation between pH–F⁻ indicates that F⁻ in the groundwater increases with pH. This is possibly due to the presence of both clay minerals (kaolinite) and fluoride-bearing minerals (e.g., biotite) in the aquifer which allow for adsorption or the release of F⁻. Under acidic conditions, the surface of the clay minerals becomes protonated, allowing fluoride adsorption, resulting in its reduction in the aqueous phase, whereas under alkaline conditions, fluoride in fluoride-bearing minerals is desorbed or exchanged with OH⁻, increasing fluoride concentrations in the aqueous phase [76]. TDS and EC positively correlated with each other and with all the other parameters except NO₃⁻ and F⁻, indicating that these two ions (NO₃⁻ and F⁻) had no significant impact on the EC and TDS. Nitrate negatively correlated with all the parameters except pH, PO₄³⁻ and Cl⁻, indicating that these parameters possibly derived from anthropogenic sources. There was also a positive correlation between all the major ions: Ca²⁺, K⁺, Mg²⁺, Na⁺, Cl⁻, HCO₃⁻, and SO₄²⁻. SiO₂ also correlated positively with all the parameters except pH and NO₃-. The direct correlation between Ca²⁺–HCO₃⁻ and Mg²⁺–HCO₃⁻ agrees with the results presented in the Piper diagram (Figure 2). Furthermore, the high positive correlation between Ca²⁺, K⁺, Mg²⁺, Na⁺, and HCO₃⁻ confirms the weathering of silicate minerals in the study area. The positive correlation between F⁻ and SiO₂ is also indicative that F⁻ originated from silicate weathering. There was a weak negative correlation between Ca²⁺–F⁻, Mg²⁺–F⁻ and Na⁺–F⁻ and a positive correlation between F⁻–HCO₃⁻. Except the inverse relationship between Na⁺ and F⁻, the observed relationships between F⁻ and the other parameters are all consistent with the findings of other researchers, e.g., [77]. Chidambaram et al. [78] noted that elevated HCO₃⁻ contents favor F⁻ release from rocks into groundwater while high Ca²⁺ concentration generally reduces dissolved F⁻ concentrations via precipitation as fluorite (Equation (17)). Apambire et al. [54] indicated that Na⁺ in groundwater generally correlates positively with F⁻. This is because, geochemical processes that increase Na⁺ concentration also directly or indirectly increase F⁻ content (e.g., Equation (18)). Therefore, the inverse correlation between Na⁺ and F⁻ could be due to the removal of Na⁺ by Ca²⁺ via reverse cation exchange, as shown in Equation (13.)

$${\mathrm{Ca}}^{2+}+2{\mathrm{F}}^{-} \to \underset{\mathrm{Fluorite}}{\underbrace{{\mathrm{CaF}}_2}}$$

(17)

$${\mathrm{CaF}}_2+{ \mathrm{Na}}_2{\mathrm{CO}}_3 \to {\mathrm{CaCO}}_3+2{\mathrm{Na}}^{+}+2{\mathrm{F}}^{-}$$

(18)

The results of the principal component analysis are presented in

Table 5. Principal component analysis (PCA) of the groundwater samples.

Parameters	PC1	PC2	PC3
TDS	0.98	−0.09	−0.12
EC	0.98	−0.16	−0.01
Ca	0.96	−0.21	−0.15
Mg	0.93	−0.09	0.19
Na	0.89	−0.07	−0.13
K	0.83	0.28	0.22
Cl	0.92	−0.33	−0.12
HCO3	0.89	0.25	0.13
PO4	0.14	−0.18	0.96
SO4	0.68	0.47	−0.09
F	−0.11	0.92	0.07
SiO2	0.77	0.33	−0.05
Eigenvalue	7.93	1.55	1.10
%Total variance	66.09	12.89	9.17
Cumulative eigenvalue	7.93	9.48	10.58
Cumulative % variance	66.09	78.98	88.15

. Three principal components (PCs) with eigenvalues > 1, explaining 88.15% of the total variance in the dataset were extracted. NO₃⁻ and pH were considered redundant parameters and were therefore dropped from the analyses because they recorded low and negative communalities, respectively. PC1 explained 66.09% of the total variation and was loaded with EC, TDS, K⁺, Ca²⁺, Cl⁻, HCO3⁻, Na⁺, Mg²⁺, SO₄²⁻, and SiO₂. K⁺, Ca²⁺, HCO₃⁻, Na⁺, Mg²⁺, and SiO₂ are associated with silicate weathering. The presence of Cl⁻ and SO₄²⁻ in this component suggests input from anthropogenic sources such as irrigation return flows or domestic waste disposal. Therefore, PC1 can be attributed to both natural and anthropogenic factors. PC2 and PC3 explained about 12.89% and 9.17%, respectively, of the total variance. PC2 was strongly loaded with F⁻ and weakly loaded with SiO₂, whereas PC3 was strongly loaded with PO₄³⁻. Fluoride in groundwater can originate from natural sources such as weathering of fluoride-bearing silicate minerals or anthropogenic sources such as phosphate fertilizers [79]. However, the correlation between the F⁻ and PO₄³⁻ was negative, suggesting that F⁻ neither derived from the application of phosphate fertilizers nor from F⁻ and PO₄³⁻-bearing minerals such as fluorapatite [Ca₅(PO₄)₃F]. The weak loading of SiO₂ in this component is indicative of silicate weathering, signifying that fluoride possibly derived from natural sources such as fluoride-bearing minerals (e.g., fluorite and biotite) in the host rocks. This is consistent with results of the analysis of the data with the Pearson’s correlation matrix. PC2 can, therefore, be attributed to natural factors. The relatively high F⁻ concentrations in the groundwater thus suggests that conditions that favor the dissolution of these fluoride-bearing minerals are present in the study area. Similar to F⁻, PO₄³⁻ in groundwater can derive from both geogenic and anthropogenic sources. Geogenic sources include phosphate-bearing minerals such as apatite, while phosphate fertilizers, animal waste, and leaking septic tanks are major anthropogenic sources of phosphate in groundwater [80]. PO₄³⁻ most likely originated from phosphate fertilizers, since it shows a low correlation with parameters that derived from geogenic or natural sources. Therefore, PC3 can be attributed to anthropogenic factors. The results of the analysis of the water samples with the PCA, therefore, show that both anthropogenic and natural factors affect the groundwater quality in the study area.

3.5. Drinking Water Quality

The chemical quality of the groundwater in the study area for drinking purposes was assessed based on the WQI values, which are usually categorized into five classes, as shown in

Table 6. Classification of the water quality index (WQI).

WQI Range	Category
<50	Excellent water
50–100	Good water
100–200	Poor water
200–300	Very poor water
>300	Unsuitable water

[81]. As depicted in

Table 7. Suitability of the groundwater for drinking purposes based on the water quality index (WQI).

Borehole	WQI	Category
BH 1	67.70	Good water
BH 2	58.63	Good water
BH 3	67.98	Good water
BH 4	61.28	Good water
BH 5	39.77	Excellent water
BH6	50.53	Good water
BH7	64.29	Good water
BH8	37.86	Excellent water
BH9	45.32	Excellent water
BH10	35.97	Excellent water

, 40% of the sampled wells have excellent groundwater quality, while the remaining 60% are classified as water of good quality. The slight deterioration in quality of the samples in the good water category is mainly due to the relatively high F⁻ or TDS values of those samples. In general, the groundwater in the study area can be described as suitable for drinking purposes.

3.6. Irrigation Water Quality

The various classifications of the parameters used to determine the suitability of the groundwater for irrigation are presented in

Table 8. Indices for determining the suitability of the groundwater for irrigation.

Parameter	Range	Quality Ratings	Percentage of Samples (%)
TDS (mg/L) [43]	<1000	Satisfactory	100
	1000–2000	Fair	–
	>2000	Inferior	–
EC (μS/cm) [40]	0–250	Excellent	–
	250–750	Good	90
	750–2250	Permissible	10
	2250–5000	Unsuitable	–
%Na [42,83]	<20	Excellent	100
	20–40	Good	–
	40–60	Permissible	–
	60–80	Doubtful	–
	>80	Unsuitable	–
MR (%) [44]	<50	Suitable	90
	>50	Unsuitable	10
PI [41]	<25	Unsuitable	–
	25–75	Moderately suitable	100
	>75	suitable	–
SAR [40]	<10	Excellent	100
	10–18	Good	–
	18–26	Fair	–
	>26	Poor	–

. In terms of TDS, groundwater is considered satisfactory if the TDS is less than 1000 mg/L, fair if the TDS is between 1000 and 2000 mg/L, and inferior if the TDS exceeds 2000 mg/L. Based on the TDS of the samples (165–524 mg/L), groundwater in the study area is considered satisfactory for irrigation purposes. The EC is a good indicator of salinity risk to crops, as it reflects the salt content in groundwater. High salt concentrations in irrigation water increase the salinity hazard or osmotic pressure of the soil solution [82], which can directly affect plant growth, soil structure, permeability and aeration. High EC indicates that less water is available to plants. The results showed that 90% of the samples had EC ranging from 275 to 556 μS/cm, indicating that they are of good quality for irrigation, while the EC of the remaining 10% fell in the permissible category. Groundwater in the permissible category may negatively impact many plants including sensitive crops. In such cases, careful salinity control procedures and the selection of plants with high salt tolerance are required.

The percent sodium (Na⁺ %) measures the Na+ content in relation to Ca²⁺ and Mg²⁺ in the water. According to Fipps [83], irrigation water containing > 60% of Na⁺ can result in the accumulation of Na⁺ in soils. This can cause soil aggregates to disperse and subsequently reduce its permeability, restricting air and water circulation in the root zones, as well as affecting the translocation of nutrients to the aerial parts of the plants, resulting in leaf senescence and/or defoliation [84]. In the present study, the Na⁺ levels in the groundwater samples were all below 20% (i.e., 9.05–17.74%), indicating that Na⁺ is not present at levels that can be harmful to plants and soils.

The MR ranged from 29.25 to 53.30%. Ninety percent of the samples had MR < 50% with the remaining 10% being greater than 50%. This suggests that, in terms of Mg²⁺, the groundwater is generally suitable for irrigation purposes. Soil permeability refers to the ability of soil to transmit water to plants. It can be affected by the long-term use of irrigational water rich in Na⁺, Ca²⁺, Mg²⁺, and HCO₃⁻. The effect of irrigation water on soil permeability can be indicated by the PI [41]. As shown in Table 8, the calculated PI for all the water samples fell within the moderate PI range (25–75%), indicating that the quality of the groundwater as far as its effect on soil permeability is acceptable for irrigation. The moderately high PI values are due to the high levels of HCO₃⁻ in the groundwater.

The SAR is also used to determine whether or not the sodium content of the irrigation water will trigger reverse ion exchange, whereby Ca²⁺ and Mg²⁺ at the exchange sites of the soil matrix are replaced by Na⁺ in the groundwater. The adsorption of Na⁺ on the soil surface makes the soil heavier and less permeable. The higher the SAR, the less suitable the water is for irrigation. According to Suarez et al. [85], as the SAR values rise, the aggregate stability and soil water conductivity both declined. As shown in Table 8, the SAR values were < 10 (i.e., 0.20–0.51), indicating that the groundwater samples are of excellent quality for irrigation.

Both the United States Salinity Laboratory Staff (Figure 10A) and the Wilcox (Figure 10B) plots also show that the groundwater in the study area is generally suitable for irrigation. In the case of the Wilcox plot, the samples fell in the C1–C3 category, indicating low to high salinity hazard. Only one sample, however, fell in the category C3 (high salinity hazard). According to Wilcox [42], the samples in category C3 can be used for irrigation but with some management to minimize the salinity effects.

3.7. Health Risk Assessment (HRA)

Although the WQI showed that the waters are generally good for drinking purposes, fluoride levels exceeded the recommended limits in all the samples. Therefore, an HRA was performed to ascertain whether or not the concentrations of fluoride in the groundwater will trigger noncarcinogenic health effects. The estimated CDI_ingestion and _HQingestion demonstrated, respectively, the level of exposure to fluoride and the health risk associated with drinking fluoride-contaminated water from the boreholes, summarized in

Table 9. Chronic daily intake (CDI) of fluoride and hazard quotient (HQ) for adults and children for noncarcinogenic risk assessment.

Borehole	Adult		Children
	CDI (mg/kg/Day)	HQ	CDI (mg/kg/Day)	HQ
BH1	0.20	3.40	0.78	13.00
BH2	0.17	2.78	0.64	10.60
BH3	0.18	2.93	0.67	11.20
BH4	0.16	2.72	0.62	10.40
BH5	0.08	1.36	0.31	5.20
BH6	0.06	1.06	0.24	4.04
BH7	0.07	1.16	0.27	4.42
BH8	0.06	1.00	0.23	3.80
BH9	0.06	1.07	0.25	4.10
BH10	0.06	1.04	0.24	3.96

. The CDI ranged from 0.06 to 0.22 mg/kg/day for adults and 0.24 to 0.78 mg/kg/day for children. This suggests that the daily exposure of children to F⁻ via ingestion is higher than that of adults. For both adults and children, however, HQ > 1 was obtained for all the boreholes, suggesting that drinking groundwater from any of the investigated boreholes will pose noncarcinogenic health hazards related to fluoride such as dental fluorosis, osteoporosis, arthritis, and thyroid to both adults and children [66]. The noncarcinogenic health risk to children is, however, higher than to adults. Similar results were also reported by [34] for nearby communities in the region. Based on these results, defluoridation of the groundwater to bring the fluoride levels up to the WHO guideline value of 1.5 mg/L is imperative to avert the associated health risk to children.

4. Conclusions

In an effort to achieve SDGs 2 and 6, ten (10) boreholes were recently drilled in some communities in the Upper East Region of Ghana to supply the residents with groundwater for drinking and irrigated agriculture. This study examined the physicochemical characteristics and quality of the groundwater in terms of its suitability for drinking and irrigation purposes, as well as the processes influencing the groundwater chemistry for its sustainable use and management. The results indicate that all the examined physicochemical parameters are within the required WHO limits, except fluoride, which concentrations grossly exceed the acceptable limit of 1.5 mg/L. The groundwater is characteristically neutral (pH 6.7–7.2), fresh (TDS < 1000 mg/L), and dominated by alkaline earth metals (Ca²⁺ and Mg²⁺) and weak acid anion (HCO₃⁻). Although there are chemical inputs from anthropogenic sources, weathering of silicate minerals and cation exchange processes are postulated as the major solute acquisition mechanisms that control the concentrations of the chemical constituents of the groundwater in the study area. Water from all wells is saturated with quartz and amorphous silica while fluorite saturation is observed in 40% of the wells. This is attributed to two main processes: the dissolution of fluoride-bearing minerals and incongruent weathering of silicate minerals (kaolinization). The study also revealed that, while the groundwater can be used for drinking purposes, the fluoride concentration must be reduced to the required level (1.5 mg/L) to avoid fluoride-related health problems such as dental and skeletal fluorosis. Similarly, based on the EC, SAR, Na%, and PI, the majority of the samples are classified as excellent and suitable for irrigation. In some boreholes, however, high salinity levels are observed, indicating that the groundwater must be treated or managed prior to use for irrigation to minimize the effects of salinity on both plants and soil.