Coupling hydrochemical characterization with geospatial analysis to understand groundwater quality parameters in North Central Nigeria

Monitoring and identifying sources of water contaminants necessitate research into hydro-chemical interactions and the health of groundwater resources. Sixty (n = 60) representative samples of groundwater in Makurdi metropolis were evaluated utilizing hydro-geochemical characterization and GIS methodologies. The region’s groundwater quality was monitored using a GIS-based water quality index (WQI). To identify the variance in hydro-geochemical facies and to understand the functional sources of chemical constituents, Piper trilinear diagram was produced. The test results revealed that the groundwater is very alkaline in nature. For each measure, the majority of the samples fell within the desirable and maximum permissible ranges set by the Nigeria Standard for Drinking Water Quality (NSDWQ) and World Health Organization (WHO). According to the Piper diagram, 86.67% of the samples are of the Na+—K+—HCO32− type, indicating alkali carbonate, while 13.33% are of the Na+—K+—Cl−—SO42− type, indicating salinity. In 100% of the samples, alkalis outnumber alkaline earth, and weak acid outnumbers strong acid in more than half (86.67%) of the groundwater samples. According to the water quality index (WQI), 93% of locations have excellent or good-quality water, whereas 7% of sites have poor-quality water. The permitted limits for TH, Na + , Cl, NO3, and SO42 are exceeded by the WQI values. The present investigation indicates significant dominance of agriculture and rock weathering capable of influencing the groundwater chemistry in Makurdi metropolis. Anthropogenic activities which can result in groundwater quality deterioration should be curtailed to avoid widespread of groundwater pollution.


Introduction
Water is essential for all life and plays a crucial role in the human lifestyle and well-being (Rajiv et al. 2012). Potable water is necessary for healthy physiological function and human survival, as many public health issues stem from poor water and sanitation (Kerketta et al. 2013). When it comes to meeting basic human requirements, the quality of water is just as crucial as the quantity (Jakeman et al. 2016;Han 2003;Howard et al. 2006;Villholth 2010). According to Yisa and Jimoh (2010), recent research has revealed an increase in the demand for freshwater as a result of rapid population expansion and the rate at which industrialization has increased in recent decades. According to the United Nations Educational Scientific and Cultural Organization, Nigeria has suffered from a lack of water supplies, forcing residents to rely on drinking water from wells and boreholes (UNESCO 2000). As a result, Nigeria began a National Borehole Program through the International Drinking Water Supply and Sanitation Agency, which included the installation of 760 boreholes, only 228 (30%) of which were productive (Akujieze et al. 2003). Groundwater is one of the most important renewable and widely distributed resources on the planet, as well as a major source of water for drinking, agriculture, and industrialization. A number of environmental issues have arisen as a result of the fast-growing population, including groundwater quality degradation (Selvam 2012). Furthermore, the quality of groundwater is deteriorating as a result of the increased use of groundwater to meet the growing population's need for drinking water (Ramakrishnaiah et al. 2009).
The interaction of soil particles, minerals precipitation, water recharge, dissolution of basement rocks, complementary action from other aquifers, and anthropogenic sources has been used as a tool for water quality outlook (Aly 2015; Das and Nag 2017; Pazand et al. 2012;Vázquez Suné et al. 2005). Hydrogen ion concentration (pH), total dissolved solids (TDS), total hardness (TH), and all main cations and anions are considered chemical characteristics of groundwater. The water quality index (WQI) is a useful tool for expressing water quality by combining multiple water quality metrics (Abbasi and Abbasi 2012). Various studies have been conducted to determine the state of groundwater, its suitability for agricultural and domestic uses, and the level of treatment necessary before use (Assubaie 2015;Cao et al. 2014;Emenike et al. 2016;Golchin and Moghaddam 2016;Nazeer et al. 2014;Rasool et al. 2016;Tenebe et al. 2016;Zaidi et al. 2016).
GIS (Geographical Information System) is a useful tool for determining groundwater quality and for monitoring environmental changes. It's been frequently utilized for assessing various groundwater applications all around the world (Sadat-Noori et al. 2013;Das 2019;Adimalla et al. 2020). Integration of geographic information systems (GIS) and remote sensing (RS) techniques is a powerful tool for ensuring water quality and monitoring accuracy. In addition, the use of thematic layer maps, GIS, and RS technologies has made it easier to comprehend the chemistry of groundwater (Selvakumar et al. 2014;Yidana 2010). The hydro-chemical examination of the concentration of groundwater quality parameters has received less attention in the research area. As a result, the focus of this research is on the geospatial analysis and hydrochemical characterization of groundwater quality indicators in Makurdi.

Study area
Makurdi town is the headquarters of Makurdi Local Government area and the capital of Benue State. The town is located between longitudes 8° 20' and 8° 40' E and latitudes 7° 40' and 7° 50' N. The town is situated astride River Benue in North Central Nigeria, about 300 km south of Jos and 450 km from Enugu in the South. The city stretches from the Nigerian Airforce base in the East along Gboko road to Adaka village along Ankpa road in the West. In the South, it is bound by Apir Village, while in the North, it is bound by Agan toll gate. It is situated in the Benue valley in the North Central region of Nigeria. It is traversed by river Benue. Vegetation in the study area is the Sudan savannah type characterized by tall grasses and short trees. The vegetation is sustained by the tropical climate that is characterized by alternating hot, rainy seasons (April to October) and cool, dry seasons (November to March). The temperature in Makurdi is generally high throughout the year, with February and March as the hottest months (Ologunorisa and Tor 2006). Makurdi is inhabited by many tribes with a population of 297,398 to 157,295 males and 140,103 females (FGN 2007). Makurdi town is a built-up area with the highest concentration of people in High Level and Wadata. A dense population also exists in some low-lying parts of the town such as Wurukum. In terms of geology, Makurdi town is composed of sedimentary rocks, of which sandstones are the dominant rock type (Kogbe 1989).

Data collection
Prior to the study, a well inventory survey was conducted to gather preliminary information about the well distribution in Makurdi metropolis. A total of 96 wells were investigated, with 60 ( Fig. 1) chosen randomly as representative wells for groundwater sampling. Clean 500 mL polyethylene bottles were used to collect groundwater samples. Before sampling, the sampling bottles were soaked in a 1:1 diluted HCl solution for 24 h and washed twice with distilled water. In the field, the bottles were washed again with groundwater sample filtrates before transporting it to the laboratory for physico-chemical analysis. Water samples were collected in bore wells after pumping the water for a sufficient amount of time to ensure the collection of formation water. Water samples were collected 30 cm below the water level in the case of open wells.

Data analysis/interpretation
Grapher software package and MS Excel spreadsheet were used for the preparation of piper trilinear and bivariate plots, Page 3 of 17 100 respectively. While origin software was used for the box plot. Furthermore, the research evaluations included the inverse distance weight (IDW) interpolation methods, and the study area was mapped to UTM Zone 32N.

Water quality index (WQI)
The Water Quality Index (WQI) is a central parameter for determining groundwater excellence for human consumption  (Avvannavar and Shrihari 2008;Mishra and Patel 2001). It is defined as a method of ranking that provides a combined control of major water quality parameters on the overall excellence of water for human consumption (Avvannavar and Shrihari 2008; Mishra and Patel 2001;Singh et al. 2016). The Water Quality Index (WQI) is a tool for determining the physical, chemical, and biological characteristics of water for drinking and household use (Wanda et al. 2013). As a result, WQI was utilized to determine the hydro-geochemical characterization of groundwater and its acceptability for drinking purposes using Nigeria Standard for Drinking Water Quality (NSDWQ 2015).
The WQI has been calculated in four steps: 1. Special weights (wi) were assigned to each elemental characteristic on a scale of 1 (lowest impact on water quality) to 5 (greatest impact on water quality), based on their alleged impact on primary health and relative magnitude in drinking water quality (Table 1) (Sener and Davraz 2013). The factors with the greatest health impact and whose occurrence over the critical concentration amount could result in the resource's use for household and drinking purposes being restricted were given the highest weight five (5) (Varol and Davraz 2014). TDS, fluoride, chloride, nitrate, sulfate, and sodium are the most essential indicators in determining water quality. Hence, they were given the highest weight (5). (Tiwari et al. 2017;Vasanthavigar et al. 2010). The bicarbonate was given the lowest weight of one (1) because it serves no purpose in the evaluation of water quality. Other characteristics, such as pH, calcium, and magnesium, were given a value of three (3), while overall hardness and potassium were given a value of two (2).
2. The relative weights for each criterion were calculated using the equation belowwhere W i shows relative weight, w i is the weight of each criterion, and n is a number of criteria. 3. The quality rating range (qi) was derived by multiplying the value of each parameter sample (Ci) by the relevant NSDWQ (2015) standards (Si) and multiplying by 100.
4. Lastly, sub-index (SI i ) was calculated using relative weights (W i ) and quality rating scale (qi) for determination of WQI. Hence,

Geospatial techniques for groundwater investigation
The Geographic Information System (GIS) is a strong tool for spatial analysis and map development, and it's commonly utilized for groundwater evaluation (Khan and Jhariya 2018;Das et al. 2017;Adimalla et al. 2020). IDW is easy to compute and is widely available among common softwares (QGIS, ArcGIS, SAGA, and GIS) and languages (R, Python, and MATLAB) while Kriging interpolation technique is the most commonly used geostatistical approach for spatial interpolation. It relies on a spatial model between observations to predict attribute values at unsampled locations. One of the specialties of kriging method is that they not only consider the distance between observations but they also intend to capture the spatial structure in the data by comparing observations separated by specific spatial distances two at a time. In several areas, the inverse distance weighted (IDW) and kriging interpolation techniques are employed for environmental spatial assessment (Zolekar and Bhagat 2020). The IDW approach assumes that the value of an attribute 'z' at some unvisited position is a distance weighted average of data points occurring within a neighborhood or window surrounding the unvisited point, making it more exact and superior to kriging and Spline (Karydas et al. 2009). As a result, IDW was employed in the current study to create thematic interpolated maps (WQI) in ArcGIS software.

Variation in hydrochemical parameters
The descriptive statistics of these parameters have been supplied in Table 2 to aid an in-depth analysis of the laboratory data. The ability of water to react with acidic or alkaline compounds in water is measured by its pH (Islam et al. 2017). It is a regulating factor that regulates the types of ions present in water and the balance between carbonate, carbon dioxide, and bicarbonate (Sadat-Noori et al. 2013;Hem 1985). The pH range measured was 6.2-7.64, with an average of 7.15 and a skewness of -0.8107. (Table 2). This means that a higher percentage of the water samples was in the pH range of the base. In reality, the water samples were slightly alkaline in 80 percent of the cases. The pH levels in the research region are within the acceptable range (6.5-8.5) and hence indicate that the water is safe to drink (Fig. 2). Total dissolved solids (TDS) can be used to determine the potability of water on the spot (Sharma et al. 2016). TDS levels in water are determined by the chemical composition of the water and the solubility of the aquifer materials through which it flows. TDS levels are the highest in sample site 4 (395 mg/L) and the lowest in sample location 11 (32.7 mg/L), with an average of 193.06 mg/L. (Table 2). TDS levels in the study region did not exceed the 500 mg/L maximum allowed limit. Ion exchange, evaporation, sediment dissolving, and rainwater penetration, according to Aghazadeh et al. (2016), can all contribute to high TDS and electrical conductivity (EC). TDS levels in groundwater can potentially be influenced by the application of agrochemicals in large quantities. According to Sharma et al. (2016), excessive levels of groundwater TDS could be caused by dissolved salts from the unsaturated zone. The high amounts of TDS found in the groundwater samples examined should be a cause for alarm. TDS levels beyond a certain threshold have been shown to cause gastrointestinal discomfort and laxative effects (Selvakumar et al. 2014). The potability of the water samples was also assessed using Davis and De Wiest's (1966) classification. Total hardness reduces the capacity of water to lather, resulting in water and detergent waste during laundry (Davis and De Wiest 1966). The total hardness (TH) of the groundwater samples tested ranged from 40 to 510 mg/L, with a mean of 248.75 mg/L. (Table 2). At 6.25 percent of the examined sample, the hardness value surpasses the maximum

Cation chemistry
The amounts of key positive ions (Ca 2+ , Mg 2+ , Na + , and K + ) were measured in order to better understand groundwater hydro-geochemistry. Ca 2+ and Mg 2+ ions in alkaline earth ranged from 0 to 48 mg/L and 3 to 21 mg/L, respectively, with a mean of 26.75 mg/L and 11.13 mg/L (Table 2). They are both within the permissible limit of 75 mg/L and 30 mg/L, respectively, as recommended by WHO (2011) andNSDWQ (2015). The concentrations of Na + and K + ions varied from 52.8 to 503.25 mg/L (mean value of 197.16 mg/L) and 2.4 to 40 mg/L (mean value of 21.64 mg/L), respectively as shown in (Table 2). The high levels of Na + could be due to the erosion of salt deposits from sodium-bearing rocks, groundwater pollution by sewage, and irrigation. The sodium concentration in 43.33% of the samples was greater than 200 mg/L. Although the presence of Na + at high concentrations in drinking water poses no major health risk, it can deteriorate soil structure and lower agricultural production if the water is utilized for irrigation (Islam et al. 2017).

Anion chemistry
The concentrations of main anions were used to examine the hydrochemistry of groundwater (i.e., HCO 3 − , Cl − , SO 4 2− , NO 3 − , and F − ). The concentrations ranged from 28 to 420, 32 to 305, 9 to 175, 1.7 to 132, and 0.13 to 1.16 mg/L, with a mean of 227.56, 119.50, 71.13, 53.70, and 0.53 mg/L, respectively. Major ions in groundwater were found in the following order: HCO 3 > Cl > SO 4 > NO 3 > F for anions, contributing 48.17, 25.30, 15.06, 11.37, and 0.11 percent of the total anion content, respectively. Chloride (Cl − ) is a small constituent of the earth's crust (Shanthi et al. 2002); its level was within the maximum permitted limit in 96.67 percent of the samples. However, in the study conducted by Balakrishnan et al. (2011), the chloride content in their samples was above the ideal limit of 250 mg/L, indicating that the groundwater may have a perceptible salty taste. Weathering of rock, atmospheric deposition, landfill leachates, septic tank effluents, poor sanitary conditions, chemical fertilizers, and industrial effluents in sewage could all contribute to greater chloride concentrations (Samantara et al. 2017). Sulfate SO 4 is found in large amounts in groundwater and does not constitute a health risk at levels found in drinking water. Its increasing content in drinking water, on the other hand, signals declining water quality, which could pose a health risk. The oxidative weathering of sulfide is the most typical source of minerals such as pyrite (FeS 2 ). Gypsum and anhydrite, on the other hand, are substantial sulfate sources in water (Han et al. 2013). The NSDWQ guideline threshold for nitrate (NO 3 − ) in drinking water was exceeded in 53.33% of the samples. Excess NO 3 − in drinking water can cause a variety of problems in children and adults, including methemoglobinemia, stomach cancer, goiter, and hypertension (Mjumdar and Gupta 2000). The main sources of nitrate contamination include anthropogenic activities, such as septic tanks, seepage beds, municipal or domestic sewage, and nitrogenous trash. As a result, multiple studies used a variety of approaches to remove it from groundwater (Qu et al. 2015;Liu et al. 2016;Chu and Wang 2017). Although fluoride (F − ) is a powerful acid (Kale and Pawar 2017), the content in all groundwater samples is well within the maximum allowed limit, so there is no regional change in its concentration. According to Nawlakhe and Bulusu (1989), lower fluoride concentrations are safe for dental health, but greater fluoride concentrations are hazardous to the spinal cord, skeletal fluorosis, and ligament deformation.

Piper trilinear diagram
In the fields of hydrogeology and groundwater analysis, piper plots (also known as trilinear diagrams) are very powerful tools for visualizing the relative abundance of common ions in water samples. Although there are other plot types that can show the abundance of ions in groundwater, this plot type is especially useful because it allows you to plot multiple samples on the same plot, thus allowing for grouping water samples by groundwater facies and other criteria. When groundwater is so closely monitored, it is especially important to have a plot type like the piper plot that makes it easy to determine whether it is suitable for human use (Piper 1944).
The Piper diagram's triangular cationic zone revealed that all of the groundwater samples (100%) fall into the sodium and potassium classes, but the anionic triangle revealed that about 86.67 percent of the samples fall into the bicarbonate zone. The remaining samples in the anion triangle fell into the no dominating zone (10%) and the Cl zone (3.33%), respectively (Fig. 3), with no samples belonging to the sulfate type (strong acidic zone). According to the piper plot (Fig. 3), 86.67% of the samples were of the Na-K-HCO 3 type, 13.33% of the samples were of the Na-K-Cl-SO 4 type, and 0 percent of the samples were of the Ca-Mg-HCO 3 and Ca-Mg-Cl-SO 4 kinds. The plot shows that 100% of the samples are of the type Na + K > Ca + Mg (alkalis exceed alkaline earths). As a result, alkaline earth does not surpass alkalis in any sample, and weak acid exceeds strong acid in more than half of the groundwater samples (86.67 percent). According to Magesh et al. (2012), this sort of water has minor salinity concerns and is good for drinking and agriculture. The findings also point to a sodium (Na) dominance, which could be due to rock deterioration (Xiao et al. 2015). Furthermore, as can be seen from the mixed groundwater types, numerous processes contribute to the composition of the hydro-chemical facies. The Piper plot (Fig. 3) also revealed Na + and K + dominance in the cation composition, while HCO 3 2− dominates the anion composition in the groundwater samples. Furthermore, higher concentrations of Ca 2+ and HCO 3 − may likewise be attributed to base ion exchange, where Na + in groundwater is being supplanted by Ca 2+ and Mg 2+ (Jankowski and Acworth 1998).
The plot of Ca 2+ /Mg + vs HCO 3 − / Ca 2+ (Fig. 4(a)) as suggested by Yusuf et al. 2021 depicts that the groundwater is influenced by carbonate dissolution and a fraction of silicate weathering for most of the samples. Also, the plot of Ca 2+ / Na + vs HCO 3 − / Ca 2+ (Fig. 4(b)) depicted the influence of silicate weathering and evaporate dissolution for groundwater samples (Ndoye et al. 2023). The plot in Fig. 5(a) shows that most of the samples fell along the aquiline (1:1), indicating that Ca 2+ , Mg 2+ , SO 4 2+ , and HCO 3 − were derived from dissolution of calcite, dolomite and gypsum. This is in tandem with results from the piper diagram showing that different facies influenced the water samples. Though much of the samples also fell below the aquiline, which typically suggests a substantial amount of Ca 2+ + Mg 2+ over (HCO 3 − + SO 4 2+ ). However, these samples suggests both carbonate dissolution and silicate weathering (Subramani et al. 2009).
When Ca 2+ vs Mg 2+ (Fig. 5(b)) was plotted, the result indicated an excess of Ca 2+ in some samples while an excess of Mg 2+ was noticed in most of the samples and a balance between Ca 2+ and Mg 2+ in the samples remaining. Also, the plot of Ca 2+ + Mg 2+ vs HCO 3 − (Fig. 5(c)) shows that most of the samples are below the aquiline (1:1). Hence, this excess can be produced from silicate and carbonate weathering (Ndoye et al. 2023).

Ion exchange processes
Na-Ca exchange assumes a huge part that can change cation concentration in groundwater and furthermore impact the development of hydro-chemical composition (Yusuf et al. 2021). Although different authors have proposed various methods of assessing ion exchange that controls groundwater chemistry, this study adopts the Ca 2+ + Mg 2+ / HCO 3 − + SO 4 2− ratio by (Cerling et al. 1989) reported in meq/L. when there is a higher occurrence of HCO 3 − + SO 4 2− over (Ca 2+ + Mg 2+ ), it indicates an exchange of Na + and K + from the water with Ca 2+ and Mg 2+ from the rocks (ion exchange process) while the reverse ion exchange is identified by an excess of (Ca 2+ + Mg 2+ ) over HCO 3 − + SO 4 2− (Edet et al. 2011;Fisher and Mullican 1997). In this study area, the calculated ionic ratio of the Ca 2+ + Mg 2+ / HCO 3 − + SO 4 2− < 1 is 100%, which substantiate the assertion observed using the piper diagram that majority of the groundwater with Na-HCO 3 facies went Table 3 Correlation Matrix of Parameters (n = 60) Note: Correlation coefficients are used to measure the strength of the linear relationship between two variables. A correlation coefficient greater than zero indicates a positive relationship while a value less than zero signifies a negative relationship. *P = < 0.05 and **P = 0.01

Water quality index
The Water Quality Index (WQI) divides water into five categories based on hydro-chemical parameters: excellent water (EW), good water (GW), poor water (PW), very poor water (VPW), and unfit for drinking (UDP) ( Table 4). The WQI ranges from 24.6 to 112.4, with a mean of 68.02 (Table 2). TDS, TH, Ca 2+ , Mg 2+ , Cl − , NO 3 − , SO 4 2− , and Na + all have a positive correlation with WQI. Approximately 15% of groundwater samples are classed as "excellent water" (Table 4). All hydro-geochemical parameters in these groundwater samples are less than or below the NSDWQ's 2015 designated maximum desirable level Table 5. Approximately 78% of groundwater samples studied were categorized as 'good water' (Table 4). Hydro-chemical concentrations were compared to excellent water, and all samples are within acceptable and maximum allowable levels. Approximately 7% of the groundwater samples are classed as 'poor drinking water' (Table 4). Groundwater needs to be protected from the use of chemical fertilizers and contamination by agro-based companies. The spatial distribution of the water quality index is shown in Fig. 6. While the spatial distribution of hydrochemical variation within the study area is depicted in Fig. 7.

Hierarchical cluster analysis (HCA)
HCA was used to find sites that shared a lot of similarities. For 60 groundwater samples in the research location, a dendrogram (Fig. 8) was created using Ward's approach (1963) and divided into three clusters. Approximately 91% of groundwater samples in clusters I, II, and III are similar to WQI classes PW, GW, and EW, respectively, according to cluster analysis. The findings of the groundwater study show that the majority of ground samples (47) are classed as 2nd cluster with good water quality, while 3rd cluster has excellent water quality (9), and 1st cluster has low water quality (4). The present studies make it clear that notable spatial analysis results of WQI are statistically significant.

Conclusion
After surface water (i.e., rivers), groundwater is the best option for drinking purposes in Makurdi, Benue State, Nigeria. Groundwater hydro-geo-chemical factors play an important role in determining water quality. However, excessive use of fertilizers and pesticides, home effluents, and other factors has damaged groundwater resources in some parts of the research area. Sixty (n = 60) groundwater samples were collected, analyzed, and appraised for drinking and agricultural applications in order to better understand groundwater quality. The parameters' results were compared to WHO (2011) andthe NSDWQ (2015). The main sources of hydrochemical variation in the research area were mineral dissolution from the soil and aquifer, as well as anthropogenic activities including agriculture and waste management. Piper trilinear and ion exchange processes were also used to determine the variance in hydro-chemical facies and to better understand the functional origins of chemical constituents. Agriculture is a major activity in the study area, and it is responsible for significant increases in TH, Na + , Cl − , NO 3 − , and SO 4 2− levels. Out of 60 samples studied, 86.67% were Fig. 4 a,  classified as Na + -K + -HCO 3 2− , indicating alkali carbonate, while 13.33% were classified as Na + -K + -Cl − -SO 4 2− , indicating salinity. In 100% of the groundwater samples, alkalis outnumber alkaline earth, and weak acid outnumbers strong acid in more than half (86.67%). According to the WQI, 15% of groundwater samples fall into the 'excellent water' category, 78% into the 'good water' category, and 7% into the 'poor water' category, and can be used for a variety of applications. The spatial distribution analysis of groundwater quality in the research area revealed that some of the samples taken did not meet the WHO (2011) and NSDWQ (2015) drinking water quality requirements. The findings revealed the importance of informing the people, local officials, and the government about the possibility of increased groundwater contamination if activities leading to the contamination persist.