Quality valuation and hydrogeochemical features of groundwater in university campus and its surroundings, south-west Nigeria

Abstract

Groundwater is an important freshwater source that can be utilized for domestic and many more purposes. This study assesses the quality and hydrogeochemical processes of shallow aquifer units in the Federal University of Agriculture, Abeokuta (Nigeria) and its localities. Groundwater chemistry, multivariate statistical techniques and water suitability indices have been utilized to appraise groundwater quality. To achieve the objective, hydrochemical analysis, water quality index (WQI), irrigation potential index (IPI) and corrosivity index (CI), have been studied. Thirty groundwater samples were drawn from hand-dug wells and analyzed for physico-chemical parameters using standard laboratory methods. Most of the tested quality parameters fell within the global health regulatory organization recommendations for safe potable water. The average abundance order of dominant cations and anions are and , respectively. Subtle alterations in groundwater chemistry were attributed to silicate weathering, ion exchange reaction and slight localized human-induced inputs. Hydrochemical facies analysis using a Piper diagram showed that the dominant groundwater type were and mixed , typically associated with rock-water interaction, and recently recharged groundwater influenced by silicate rock dissolution. By the WQI results, 97% of the groundwater samples belong to ‘excellent to good’ category while the remaining 3% (sample OS2) belongs to ‘poor’ water quality. In terms of agricultural usability, over 50% of the groundwater samples were deemed suitable for irrigation. However, concerns were noted in relation to sodium percentage (Na%), soluble sodium percentage (SSP) and kelly ratio (KR), which could impact soil health over prolonged use.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-41764-0.

Introduction

Groundwater is a kind of natural water resource found within the aquifer matrix and accounts for roughly 97% of the existing freshwater resources worldwide^1–3. It is considered the most practical source of freshwater that greatly assists in meeting the demand for water supply by the population in most countries worldwide. Groundwater is vital to humans as it is utilizable for several drives such as consumption, agricultural, and manufacturing usages^4–7. The quality of aquifer system is influenced by natural and human-origin inputs^4,8,9. Factors such as climate, geological settings, land use patterns and release of contaminants to the immediate environment had considerable impacts on overall quality of aquifer systems^8,10,11. A major threat to groundwater resources is the deterioration in quality due to contaminants derived from several anthropogenic inputs^8,12,13. Anthropogenic activities contribute significantly to groundwater pollution in many developing countries, including Nigeria. The quality of groundwater is decisive for its aptness for various purposes and is of utmost important to environmental scientists, water resources managers, agriculturists, and industrialists^7,9,11,14. Groundwater quality can be compromised by the infiltration of pollutants into the shallow water table, leading to changes in its inherent physical–chemical properties, thus affecting its potability and suitability for other uses^15,16. Quality requirements vary according to the explicit mission. Water fit for consumption and irrigation purposes must meet certain recommendation restrictions set by recognized regulatory agencies such as World Health Organization (WHO) and Food & Agricultural Organization (FAO), while water intended for industrial use should be devoid of contaminants that could influence corrosion rates and formation of scale^17,18.

Quality ranking can be inferred through the concentrations of different physicochemical variables embedded in the groundwater system. These parameters change widely as a result of various types of pollutions due to anthropogenic activities, seasonal variation and extent of groundwater extraction^1,8,19. Most importantly, the rise in anthropogenic activities near aquifer sources over the years has led to the potential release of contaminants into available shallow groundwater sources, thereby making them unfitting for domestic purposes¹¹. Some typical examples of anthropogenic inputs that impede the quality of water include careless industrial wastewater discharge, indiscriminate disposal of household wastes beside groundwater source, release of untreated effluents into the environment, excessive use of agricultural chemicals near aquifer sources as well as siting of lavatories and bathrooms near shallow dug wells^14,20. Adequate information about the hydrochemical composition of aquifer system in a local context assists in pinpointing potential origins of dissolved ions and/or contaminants, as well as prevalent geochemical processes influencing the quality of studied groundwater system^14,15. Studying hydrochemical processes that influence groundwater chemistry in a particular area can conspicuously differentiate the extent of contribution by both anthropogenic inputs and natural rock-water interactions to overall groundwater quality^20–22. Corrosion occurs when water reacts with or dissolves metals in the water stored or flowing through the distribution system, leading to the leaching of metals and other contaminants into drinking water^14,23,24. This process usually results in equipment and water distribution system (WDS) degradation, cavity formation, worsening of water potability and weakening of human health¹⁸. Scale formation results from the reaction of divalent cations (Mg²⁺ and Ca²⁺) with carbonate and hydrogen carbonate compounds in saturated water, bringing about sediment deposition in distribution pipes or water heaters^14,23,24. Determining the stability status of aquifer units is complex and interactive, requiring the use of multiple indices to assess water stability for industrial use, such as the langelier saturation index, larson-skold, ryznar index, puckorius scaling index, aggressiveness index, and Chloride to Sulfate Mass ratio²⁴.

Agriculture has been a foremost impetus sector and a cornerstone in the overall value of domestic income of greatest nations of the continent, and thus the groundwater for watering uses must be free of pollutants and be of status harmless to crop growth /development and crop yield¹⁷. Hence, a resolute work is of the essence, in assessing the quality of water for wetting need by evaluating irrigation parameter indices^3,4,19.

Water drawn from shallow hand-dug wells are consumed directly or used for cooking by the densely populated students and staff of the Federal University of Agriculture, Abeokuta (FUNAAB) who are inhabitant within the University campus and adjoining vicinities. Many of the hand-dug wells within the study areas are of poor design, covered mostly with wood planks or aluminum sheet, thus making them susceptible to pollution due to human activities within the vicinity of the wells. Furthermore, considering the fact that FUNAAB is an agricultural-based university located within a peri- urban area, where water sources can be used for different needs such as consumption, agricultural and industrialized purposes by both students and staff, there is a need to appraise the quality status of available groundwater sources in the university campus and its vicinities.

Numerous published findings have been done on the hydrogeochemical investigation, drinking and wetting appropriateness of water system globally^5,8,9,19. Majority of published works on aquifer systems in the FUNAAB and its surroundings dwell more on suitability for drinking and/or irrigation purposes only^1,25. Although there was a study by²⁶ on water sources (wells, borehole and surface water) within Federal University of Agriculture, Abeokuta (FUNAAB) and its environs (limited sampling points that were not more than 3.1 km from the university campus), their findings did not include assessing the suitability of sampled water sources for drinking, agricultural, and industrial purposes. Furthermore, no preceding study on the evaluation of groundwater quality apposite for consumption, agricultural and industrial uses together with various multivariate statistical analysis has been conducted in the study locations.

Therefore, this present study systematically appraised groundwater quality and hydrogeochemical characteristics in the FUNAAB and its environs. Remarkably, this study distinguishes itself from previous research by assessing the suitability of groundwater system in the study locations for drinking, irrigation and industrial uses through indexical approach. The specific objectives are (i) determination of quality status of sampled water through physicochemical data and indexing approach (ii) determination of fitness of sampled water for consumption, irrigation and manufacturing needs (iii) determination of chemistry of groundwater in the research location and (iv) comparing the water quality status with national and international drinking standards (WHO and NIS) to ensure that it meets safety requirements.

Materials and methods

Location depiction and geographical settings

The research location is located at latitudes 7°13′40.278″ to 7°13′40. 318″N and longitudes 3°26′9.373″ to 3°26′9.992″E (Fig. 1). The study location is characterized with a rugged terrain of two basically landforms- sparingly scattered short hills and knolls and almost flatland. The software used to generate Figs. 1 and 2 was Golden Software Surfer (Version 12.0.626).

Fig. 1.

Location map of the research locations displaying the water sample sites (https://www.goldensoftware.com/products/surfer).

Fig. 2.

Geological Map of the study area displaying the groundwater sample locations (https://www.goldensoftware.com/products/surfer).

The geology of the research location overlies with metamorphic rocks of the basement complex, the majority of which are ancient being of Precambrian age with great variation in grain size and mineral composition. The lithological units include pegmatite or quartz vein coarse porphyritic biotite and biotite-muscovite granite, fine-medium grained biotite and biotite-muscovite granite and migmatite (Fig. 2). Groundwater occurrence within the study area is contained within the fractured and in-situ weathered portions of underlying rocks which are usually exploited through shallow hand-dug wells or boreholes. The major rock type underlies the study area is migmatite (Fig. 2).

Groundwater samples collection and laboratory analysis

Before water sampling, a preliminary reconnaissance survey was conducted to assess the feasibility of the study locations. This survey identified thirty (30) sampling points for groundwater samples collection. The selected locations of water sampling are FUNAAB campus and adjoining localities (FUNAAB main gate, Accord, Harmony, Isolu, Oluwo and Zoo park area), and their exact coordinates and well data are presented in Table S1. The groundwater samples were collected from thirty (30) randomly selected hand-dug wells between December, 2024 and January, 2025. The locations of the sampling points for the groundwater samples are shown in Fig. 1. The samples were collected in a 2 L plastic containers. At every water sample site, sampling container was painstakingly wetted three (3) intervals prior to the real assemblage of the water sample²⁶. Samples were labelled properly with respect to sample sites for easy identification. GPS were used to take the coordinates of sampling locations. In addition, Total well depth and water level depth were recorded (Table S1). Following collection, the water samples were put in a cooler box containing ice blocks at a temperature of less than 4°C before being transported the laboratory (SMO laboratory service) for necessary preservation within two days before the commencement of physicochemical analysis. Analysis of sample was carried out in duplicates to determine the selected physico-chemical properties according to²⁷ specifications.The physicochemical parameters of interest in this study include electrical conductivity, total dissolved solids, pH, vital major cations (Na⁺, K⁺, Ca²⁺ and Mg²⁺) and major anions (,,, and ).

The TDS, EC and DO were measured in situ using multipurpose portable digital meter (Extech DO 700) while pH readings of water samples was done by pH meter standardized with pH buffers (pH 4,7, and 10)^10,28. Turbidity was measured using the gravimetric technique. The major anions of SO₄^2- and NO₃^- were measured using ultraviolet spectrophotometric method and turbidimetric technique, correspondingly; Chloride anion was determined using silver nitrate titration method while carbonate and hydrogencarbonate ions were measured via titration process with standard acid¹⁰. For major cations, Na⁺ and K⁺ were determined using model 410 Corning clinical flame photometric method with air-butane gas mixture as oxidant while Ca²⁺ and Mg²⁺ concentrations were measured using the absorption mode of Model 210 VGP Buck Scientific Atomic Absorption Spectrometric (AAS) technique²⁹. Since the aforementioned are the most vital parameters for the appraisal of water quality index for assessing the quality of groundwater for domestic uses, hence, these parameters were selected for the valuation of groundwater quality in the study locations.

The dependability of the physicochemical data were established by computing the anion-cation balance error between the measured total cations and total anions for each collected sample, and the error value obtained for each sample was within the allowable threshold of ± 10%³⁰.

Statistical analyses of physicochemical data

Basic descriptive statistics were carried out on obtained physico-chemical data. ANOVA was performed so as to check for the level of significance or otherwise of the averages of measured physical–chemical variables in collected samples among the sampling locations. Statistical data analyses were done using the statistical software SPSS version 20.

Pearson’s correlation analysis was carried out on the physicochemical data in order to identify the degree of relationships among measured physicochemical parameters in collected groundwater samples¹⁶. The HCA was performed in accordance with agglomerative program where a blend of ward’s linkage as well as squared euclidean distances were used to quantity the connection or dissimilarity in properties of analyzed water quality- induced parameters and/or sampling locations^28,31. On the other hand, PCA was employed in order to identify significant properties/parameters that explain most of the variations of the original data set^7,31. Both HCA and PCA can be used to infer the probable sources of tested physicochemical properties and kind of impacts of measured quality-induced variables on overall groundwater chemistry^9,32. Box plots and means plots were also used in this study. Box and means plots reveal clearly the characteristics of each measured parameter with respect to each sample location⁷.

Estimation of groundwater quality index

Groundwater quality index provides a means of quantifying the overall fitness of particular aquifer system for consumption purposes based on some selected quality-induced parameters. The estimation of GWQI was solely to determine suitability of the samples for drinking. A weight is assigned to every considered physical–chemical property based on its particular impact in the general water quality for consumption use^20,33. Nitrate ion was allotted highest value of 5 due to its significant prominence in determination of potable water quality. Other parameters were assigned weight ranging from 2 to 4 dependent on their level of consequence in drinking water quality status (Table S2). The comparative weight (W_i) of every selected property was then computed by relation (1):

1

where denotes the weights apportioned for each quality-induced property.

The worth ranking gauge (q_i) for most property was calculated by relation (2) as:

2

where C_i represents concentration of each property and S_i is the WHO/NSDWQ permissible limit for each analyzed property. For pH and dissolved oxygen (DO), the quality rating was estimated using Eqs. (3 and 4), respectively:

3

4

The sub-indices (SI_i) for each property is calculated by relation (5):

5

Finally, the calculation of the water quality index (WQI) was given as:

6

The appropriateness of water for drinking purpose according to WQI values is categorized into 5 dissimilar groups as proposed by^33,34 as: excellent class = 0–25; good class = 26–50; poor class = 51–75, very poor = 76–100 while WQI greater than100 denotes unfit for drinking purpose (Table S3).

Hydrogeochemical characterization of water samples

Chloro-Alkaline indices can be utilized to effectively comprehend the type of demineralization process during the residence or travel time which ultimately affects hydrochemistry⁷. Chloro alkaline index 1 and 2 are computed by relations (7) and (8), correspondingly:

7

8

The cations and anions involved in CAI-1 and CAI-2 are expressed in meq/l. Reverse deionization (surge in content of compared to (Na⁺ + K⁺) is predominant for positive values of CAIs whereas negative values of indices suggest dominance of cation-exchange reaction¹⁰. ‘To further classify the groundwater sample, the values of base exchange index (BEI) and meteoric gneiss index (MGI) were computed via Eqs. (9 and 10) as:

9

10

BEI values > 1 (equals type) and if BEI values < 1 (denotes type). Similarly, if MGI > 1, the water origin belongs to shallow meteoric water percolation kind while MGI value < 1, indicates that the water type is of deep meteoric percolation type¹⁰.

The geochemical plot of Piper Trilinear diagram for the samples was obtained using the Aquachem scientific software version 3.7. Piper plot helps in appropriate identification of hydrochemical facies that influence the dominant hydrogeochemical reactions in an aquifer matrix^33,35.

Corrosiveness and scaling index

In this study, the following indices Larson-Skold Index (LSI), Aggressive Index (AI), Chloride-Sulfate-mass-ratio (CSMR), Langelier Saturation Index (L-S), Ryzner stability index (RSI) and Puckorius Sealing Index (PSI) were engaged to estimate the corrosivity standing of the collected groundwater samples in the research locations. The Larson-Skold Index (L-S) was calculated using the Eq. 11 as:

11

When L-S < 0.80, water has a scaling propensity; 0.80 < L-S < 1.20, corrosion intensity may be greater than anticipated; and L-S > 1.20 denotes greater rates of confined corrosion¹⁴.

The AI was valued utilizing the equation:

12

AI values greater than 12 denotes unaggressive water, 10 less than AI < 12 signify temperately aggressive while AI values < 10 suggests highly aggressive water.

CSMR evaluates the corrosive risk index especially in lead and copper pipes.

13

When CSMR values less than fifty percent; water is prone to bimetallic corrosion and.

CSMR higher thanfifty percent: water is prone to bimetallic corrosion³⁶.

The LSI, RSI and PSI are used to estimate corrosiveness and scaling tendency of water in pipes. The following equations are used to compute the corrosive indices respectively:

14

In Eq. 14, pH refers to the definite pH of sample whereas pH_saturated refers to calculated pH value at saturation state of :

15

where

where µ = 0.000025 TDS, Ca²⁺ is the calcium hardness (mg/L of CaCO₃), T stands for temperature in ^oC andTDS equal to the total dissolved solids in mg/L^24,37,38. A negative value of LSI denotes that the water is under saturated and tends to dissolve CaCO₃ while the positive value of LSI denotes that the water is supersaturated with CaCO₃ and scale formation is advocated^24,39.

According to⁴⁰, a range of (− 4 < LSI < − 2) indicates slight corrosion; range of (− 1 < LSI < 0) indicates little corrosion; LSI equals to zero indicates water that has no tendency to dissolve or precipitate CaCO₃ and range of (0 < LSI < 2) indicates little to modest scale formation.

Puckorius scaling index specifies the softening ability and precipitation features of water to attain equilibrium^41–43. It is measured by the expression:

16

where denotes the hydrogen ion concentration at saturation while is pH at balance, and is given by Eq. 17:

17

PSI value < 6 indicates water has scale formation propensity; 6 ≤ PSI ≤ 7 indicates water has slight scaling and corrosive affinities while PSI greater than 7 suggests noteworthy corrosive inclination³⁶.

RSI is employed to envisage the extent of scale deposition in phreatic water^41,42. RSI is expressed through the relation:

18

where pH and retain their usual meanings.

According to^41,43: RSI ≤ 5.50 signposts water has a severe scale formation, 5.50 < RSI < 6.20 suggests aquifer has comparatively scale formation as well as corrosion tendency, 6.20 ≤ RSI ≤ 6.80 indicates stable water while PSI > 6.80 indicates corrosive water.

Computation of irrigation potential index

Suitability of water for irrigation purpose was determined using the following irrigation potential indices: Sodium percentage ratio (Na%), Soluble Sodium Percentage (SSP), Sodium Absorption Ratio (SAR), Permeability Index (PI), Magnesium Adsorption Ratio (MAR) and Kelly’s Ratio (KR). The physico-chemical parameters involved in computation of each index were firstly converted from mg/l to meq/l. Table 1 depicts the irrigation indices equations and their classifications.

Table 1.

Irrigation indices equation and their classifications.

Indices	Equation	Range	Classification
Na%		< 20 20–40 40–60 60–80  > 80	Excellent Good Permissible Doubtful Unsuitable
SSP		< 50  > 50	Good Unsuitable
SAR		< 10 10–18 18–26  > 26	Excellent Good Doubtful Unsuitable
PI		> 75 25 – 75  < 25	Good Suitable Unsuitable
MAR		< 50  > 50	Suitable Unsuitable
KR		< unity  > unity	Suitable Unsuitable

Results and discussions

Basic statistics of the respective levels for all the assessed physico-chemical parameters in groundwater samples are presented in Table 2 and as boxplot in Fig. 3A–C. From Table 2, it was observed that parameters—turbidity, sulphate, Ca²⁺ and K⁺ have coefficient of variation (CV) greater than 50%. This probably signposted the diverse plenitude of aforementioned physicochemical properties in the sampled groundwater. However, the remaining parameters had CV < 50%, suggesting homogeneity plenitude of most physical–chemical variables in collected groundwater samples²⁶.

Table 2.

Descriptive statistics of analyzed physicochemical properties in water samples.

	N	Minimum	Maximum	Mean	Std. deviation	cv%	Variance	Skewness	Kurtosis
pH	30	6.76	7.64	7.1690	.21916	3%	.048	.090	− .308
TDS	30	41.0	281.0	115.467	55.5442	48%	3085.154	.988	1.250
EC	30	82.0	373.0	211.667	83.5523	39%	6980.989	.246	− 1.021
Turbidity	30	0.00	10.25	.9477	1.84125	194%	3.390	4.752	24.334
DO	30	4.1	7.6	5.540	.8950	16%	.801	.418	− .652
	30	102.45	156.79	124.5927	15.11000	12%	228.312	.402	− .437
Cl−	30	4.00	35.16	22.5947	7.60006	34%	57.761	− .142	− .240
	30	.74	23.94	10.2783	7.48664	73%	56.050	.513	− 1.215
	30	1.17	3.38	1.9923	.64277	32%	.413	.459	− .999
Ca2+	30	.04	32.50	5.8263	6.84907	118%	46.910	2.209	6.855
Mg2+	30	.08	.85	.7480	.19029	25%	.036	− 2.727	6.874
Na+	30	9.76	42.70	26.5553	9.05872	34%	82.060	− .180	− 1.052
K+	30	1.2	57.6	8.573	10.3050	120%	106.192	3.964	18.525

Fig. 3.

(A) Box plots of pH, EC, DO and . (B) Box plots of Cl^-, Na⁺ and . (C) Box plots of Mg²⁺, TDS, turbidity, Ca²⁺ and K⁺

The box plots of pH, EC, DO, bicarbonate, Cl⁻, Na⁺ and as depicted in Fig. 3A, B have no outliers, indicating even distribution of these properties in the groundwater samples. However, samples FS1, FS2 and FS5 stood out as outliers in the box plot of Mg²⁺ ions as their concentrations were lower than that of other remaining water samples. From the box plot of TDS, samples IS1 stood out as only outlier as its TDS concentration was higher than that of other water samples. Likewise sample HS1 stood out as the only outlier for Ca²⁺ as its value was higher than that of any other analyzed samples for this study. From the box plot of turbidity, samples AS1 and FS5 stood out as the outliers, with significant value higher than permissible limit in FS1. Similarly, samples IS3 and OS2 stood out as outliers in the box plot of K⁺ ions as its concentrations in those two samples were higher relative to that of other groundwater samples. Outliers observed in TDS, turbidity, Ca²⁺, Mg²⁺ and K⁺ suggest certain localized impacts on groundwater systems of the study locations⁴⁴.

From the mean plots (Fig. S1a–n), it was observed that the highest values of Na⁺, K⁺, Mg²⁺, , and Cl^- were recorded at GS sampling location. This location serves as the boundary between FUNAAB and its environs. Furthermore, the mean plots also revealed that lowest average values of Na⁺, K⁺, Mg²⁺, Ca²⁺, , EC, TDS and pH were recorded at FS location. However, FS location has the highest mean turbidity value. The mean plots further revealed that maximum concentrations of bicarbonate and carbonate ions together with highest mean pH were recorded at HS location whereas IS location has the maximum concentrations of average TDS as well as DO in groundwater samples. However, OS groundwater sampling site is characterized by highest mean EC concentration, but lowest concentrations of carbonate, bicarbonate, dissolved oxygen as well as turbidity. In terms of ANOVA, the ANOVA result (Table S4) shows that there is significance difference across the locations for the variables pH, TDS, EC,, ,, Ca²⁺, Mg²⁺, Na⁺ and K⁺ at p < 0.05 level of significance.

From Table 3, the pH of samples varied from 6.76 to 7.64, with an average value of 7.17 which falls within the acceptable threshold of 6.5 to 8.5 for drinking water⁴⁵. The average neutral and slightly alkaline status of samples in the study locations is different from the acidic status of groundwater samples within Bogobori community in Cross River State (South South, Nigeria) by⁶ but concurs with neutral to slightly alkaline status of groundwater systems within parts of Ibadan metropolis as well as Owerri and its environs by²⁹ and⁴, respectively. The turbidity ranged between 0.00 and 10.25 NTU (Table 3). 96.7% of total samples (29 water samples) had turbidity values lower than the allowable threshold of 5 NTU⁴⁵ while the remaining 3.3% (sample FS1) had turbidity value (10.25 NTU) greater than the permissible limit. This might be due to the fact that sample FS1 was collected from well that was recently dug this year (2025). Concentration of EC in samples varied between 82 and 373 µS/cm with an average value of 211.67 µS/cm that falls within the safe limit of 1000 µS/cm, hence appropriate for consumption and agricultural needs^10,46. In addition, EC values less than 1000 µS/cm indicates minimal influence of nearby human-induced inputs on chemistry of aquifer systems in the research sites³⁰. Additionally, 100% of the water samples belong to Type 1 (EC < 1500 µS/cm) water, indicating low enrichment of dissolved salts in water as a result of soil-rock-water interface. Total dissolved solids (TDS) follow the trends of EC because of their relationship. 100% of groundwater samples denote freshwater status (TDS < 1000 mg/L) due to natural soil-rock-water interaction, reflecting low extent of mineralization^4,47. The TDS of the groundwater samples ranged from 41 to 281 mg/l with a mean value of 115.47 mg/l which lie within the permissible standard of 500 mg/l for potable water. The concentrations of the cations: Ca²⁺ (0.04–32.50 mg/l), Mg²⁺(0.08–0.85 mg/l) and Na⁺ (9.76–42.70 mg/l) were relatively low and fall below the permissible limits of 75 mg/l, 20 mg/l and 200 mg/l, respectively for drinking water⁴⁵. The concentration of K⁺ ranged from 1.20 to 57.60 mg/l (average = 8.57 mg/l). Almost 23% of the groundwater samples have K⁺ concentration higher than allowable frontier of 10 mg/l, with OS2 sample having 5 times the WHO allowable frontier for K⁺ in drinking water⁴⁵. This could be due to nearness of OS2 well to mini dumping yard, possible use of agricultural formulations in the nearby farm^4,29. Presence of K⁺ in aquifer units can also be attributed to the presence of K- bearing silicate minerals in igneous and metamorphic rocks⁴⁸. Approximately 77% of the groundwater samples have K⁺ concentration below the permissible limit of 10 mg/l for potable water⁴⁵. This could be attributed to reluctance of most potassium-bearing minerals to decomposition process via weathering actions, coupled with the fact that during weathering, K⁺ gets fixed into clay materials²⁹. The concentration of K⁺ in water needs to be monitored as excessive intake gives off laxative effect^29,49.

Table 3.

Values of physiochemical parameters in groundwater samples.

	pH	TDS	EC	Turbidity	DO	HCO3-	Cl-	SO42-	NO3-	Ca2+	Mg2+	Na+	K+
S/code		(mg/l)	(μS/cm)	(NTU)	(mg/l)	(mg/l)	(mg/l)	(mg/l)	(mg/l)	(mg/l)	(mg/l)	(mg/l)	(mg/l)
AS1	7.22	131.00	265.00	1.99	6.70	143.56	29.57	17.31	2.23	11.49	0.83	31.72	8.80
AS2	7.19	83.00	166.00	0.66	4.10	137.89	26.44	15.47	2.21	3.66	0.83	20.74	2.80
CS1	7.18	148.00	297.00	0.18	5.80	133.76	21.06	0.74	2.56	12.18	0.84	34.77	7.20
CS2	7.46	71.00	142.00	0.68	4.90	131.85	18.76	5.34	1.57	0.47	0.73	21.35	2.00
CS3	7.18	82.00	164.00	0.00	6.40	129.65	16.12	3.87	1.65	4.49	0.83	19.52	2.80
CS4	7.14	64.00	128.00	0.15	5.30	125.45	16.56	4.79	1.47	0.22	0.72	18.30	1.20
CS5	7.07	105.00	211.00	0.44	5.40	119.67	20.09	7.74	1.96	4.11	0.85	23.79	5.20
CS6	6.88	114.00	229.00	0.07	5.30	105.38	12.03	1.11	2.08	4.73	0.83	31.72	2.80
CS7	7.04	95.00	190.00	0.66	4.30	108.23	19.34	6.08	1.86	8.94	0.82	21.96	11.60
CS8	7.08	41.00	82.00	0.59	6.00	110.09	16.43	4.05	1.25	0.90	0.70	9.76	2.80
CS9	7.25	56.00	112.00	0.15	6.80	126.17	16.08	3.32	1.43	1.76	0.80	15.86	7.60
FS1	7.06	78.00	156.00	10.25	6.10	107.54	23.45	9.03	1.56	0.04	0.08	31.11	2.00
FS2	6.76	55.00	110.00	0.52	5.20	132.45	15.96	3.68	1.39	0.35	0.38	20.74	3.60
FS3	6.81	60.00	120.00	0.44	6.20	133.06	4.00	0.92	1.42	1.78	0.76	12.81	9.20
FS4	6.82	111.00	223.00	0.52	4.80	126.23	31.09	20.81	1.17	1.16	0.81	22.57	4.40
FS5	7.01	89.00	180.00	2.29	4.90	109.56	19.35	6.26	1.33	0.24	0.19	32.94	1.60
FS6	6.88	49.00	98.00	0.15	5.40	102.45	12.16	1.66	1.37	0.52	0.69	13.42	4.40
FS7	7.12	52.00	104.00	1.03	6.60	123.78	23.15	10.49	1.43	0.86	0.75	12.20	5.60
GS1	7.43	165.00	333.00	1.70	5.00	136.27	34.56	22.29	2.68	9.62	0.85	38.43	11.20
HS1	7.64	180.00	361.00	0.96	4.70	156.79	35.16	23.94	2.89	32.50	0.84	39.04	11.60
HS2	7.47	148.00	297.00	0.66	4.60	152.44	29.23	18.60	2.54	7.78	0.85	31.72	7.60
HS3	7.52	147.00	295.00	1.03	6.50	153.09	33.92	22.10	2.46	11.45	0.85	36.60	7.60
IS1	7.16	281.00	162.00	0.44	5.10	118.79	19.87	6.45	3.38	2.58	0.82	19.52	6.80
IS2	7.31	217.00	235.00	0.59	6.20	121.03	21.68	8.47	3.15	2.82	0.83	31.72	17.20
IS3	7.23	105.00	211.00	0.15	6.90	121.06	22.79	8.66	1.25	2.72	0.83	29.28	19.20
IS4	7.25	111.00	223.00	0.59	7.60	119.86	19.88	6.63	1.32	0.80	0.77	32.94	4.80
OS1	7.05	150.00	301.00	0.44	4.30	102.93	25.67	9.95	2.26	14.35	0.84	28.67	14.00
OS2	7.12	186.00	373.00	0.15	4.80	104.78	33.08	20.67	2.76	13.52	0.84	42.70	57.60
ZS1	7.31	149.00	299.00	0.88	5.50	112.33	29.34	18.47	2.61	11.40	0.84	33.55	5.60
ZS2	7.43	141.00	283.00	0.07	4.80	131.64	31.02	19.45	2.53	7.35	0.84	37.21	8.40

Generally, the sequence of key cations concentration distribution in the collected samples in decreasing order is:, making Na⁺ the most overriding cation in the chemistry of groundwater in the study location. Similar cationic order in groundwater samples was also reported by²⁹. However, this is in contrast to the orders and in groundwater samples from Dhaka (Bangladesh) and Amman-Zarqa basin (Jordan), respectively by¹⁹ and⁵.The order of anions distribution in the samples is with as the most foremost ion in the collected groundwater samples. Similar order of anions in groundwater samples was also described by¹⁹.

Bicarbonate in samples ranged between 102.45 and 156.79 mg/l (mean = 124.59 mg/l) (Table 3). Origins of bicarbonate ions in water include carbonate dissolution, silicate weathering and release of carbon dioxide into the soil via degeneration of organic matter^4,11. Being the dominant anion, further scrutiny of the results showed that 50% of samples had more than permissible limit of (125 mg/l) for drinking water. This could be ascribed to dissolution of calcite and dolomite. The concentration of values ranged from 35.16–4.00 mg/l, 23.94–0.74 mg/l and 3.38–1.17 mg/l, respectively with mean values 54.13 mg/l, 22.59 mg/l, 10.28 mg/l and 1.99 mg/l respectively. The concentrations of the analyzed anions in all groundwater samples lie within the standard guideline values of 120, 250, 100 and 50 mg/l respectively for drinking water. Mean value of nitrate ion in groundwater samples less than 10 mg/l indicates minimal or negligible contamination from sewage effluent, septic tank and agricultural formulations^28,50.

The dissolved oxygen (DO) concentrations in the groundwater samples ranged between 4.10 mg/l and 7.60 mg/l, with an average of 5.54 mg/l (Table 3). The result showed that 63.33% of the groundwater samples have DO values greater than the permissible bound of 5mg/l for drinking while 36.67% of the groundwater samples had DO concentration that lie below the tolerable threshold for drinking purpose. The spatial distribution maps of few physico-chemical properties are presented in Figs. 4 and 5.

Fig. 4.

Spatial distribution maps of EC, , SO₄^2-, NO₃^- and Cl^-

Fig. 5.

Spatial distribution maps of Ca²⁺, Mg²⁺, Na⁺, K⁺ and pH.

Hydrochemical characteristics of groundwater samples

Geochemical evolution and ion exchange process take place deep underground between groundwater and aquifer minerals or matrix. Major cations and anions used in classification of groundwater sample are , and . The groundwater samples have and concentration < 1 meq/l whereas concentration varies from 1 to 3 meq/l, suggesting all samples be allied to usual and kind¹⁰.

From the values of BEI and MGI in analyzed groundwater samples (Table S5), 87% of the total samples had BEI values > 1, suggesting predominance of type while 13% had BEI value < 1 which indicates they belong to type. NaHCO₃ water type at depths of wells of notless than 30 m was also reported by³⁰. The source of bicarbonate ions in collected groundwater may be from carbonate mineral dissolution as well as weathering of silicate minerals¹⁹. Similarly, 87% of the groundwater sample had MGI value > 1, thus belonging to “shallow meteoric water percolation type” while the remaining 13% belong to “deep meteoric percolation type” as their MGI values are less than unity.

Identification of hydrogeochemical process

The ratio ranged between 0.813 and 4.938 (mean = 1.948) (Table 4). In 93% (i.e. 28 samples) of total samples, the ratio is greater than 1, indicating the existence of silicate weathering and ion exchange process as dominating factor influencing the quality of groundwater system in the sampling locations²⁰. However, samples CS8 and FS7 had  < 1, signifying a reverse ion exchange process/halite dissolution as other governing process of groundwater chemistry in the area^20,51,52. The calculated value of ranged from 0.185 to 23.439 meq/l with 33% of the sample having values less than one, indicating that the groundwater is enriched in compared to ⁵¹ while 67% of the sample had values larger than unity, suggesting dominance of silicate mineral weathering¹⁰. This can be further confirmed from the values of the ionic ratio having values less than 1 in all groundwater samples which suggest an indication of dominance in ion exchange. It could also be due to mixing of waters with different hydrochemical properties⁵³. The ratios are less than unity which suggests dolomite weathering, silicate minerals decomposition and deionization process¹⁰. The ratio of all groundwater samples are less than 0.50 meq/l signifying fresh water recharged by meteoric water, reflecting dominance of bicarbonate from carbonate weathering^53,54. This can be further confirmed from the ionic ratio having values greater than 2, indicating unaffected fresh groundwater, dominated by carbonate weathering with minima salinization process⁵⁴. Ionic ratio > 1 in all groundwater samples suggesting chloride-dominated water, typically arising from rock salt dissolution or localized anthropogenic factors such as fertilizer leaching⁵⁵. Chloride dominated groundwater was corroborated by ratios  < 1.00 in all samples (Table 4).

Table 4.

Ionic ratio and chloro alkaline indices for groundwater samples.

S/code									CAI 1	CAI 2
AS1	0.237	1.654	2.821	0.354	0.432	2.315	8.376	0.614	− 0.924	− 0.284
AS2	0.097	1.210	3.030	0.330	0.432	2.316	2.681	0.362	− 0.306	− 0.088
CS1	0.307	2.546	3.690	0.271	0.026	38.563	8.805	0.975	− 1.856	− 0.499
CS2	0.037	1.755	4.084	0.245	0.210	4.760	0.392	0.174	− 0.852	− 0.198
CS3	0.133	1.867	4.673	0.214	0.177	5.644	3.269	0.736	− 1.025	− 0.211
CS4	0.033	1.704	4.402	0.227	0.213	4.685	0.185	0.099	− 0.770	− 0.167
CS5	0.130	1.826	3.461	0.289	0.284	3.517	2.933	0.560	− 1.061	− 0.283
CS6	0.174	4.066	5.090	0.196	0.068	14.685	3.473	0.911	− 3.277	− 0.635
CS7	0.270	1.751	3.252	0.308	0.232	4.310	6.589	0.779	− 1.295	− 0.372
CS8	0.054	0.916	3.893	0.257	0.182	5.497	0.775	0.348	− 0.070	− 0.017
CS9	0.072	1.521	4.559	0.219	0.152	6.563	1.339	0.560	− 0.949	− 0.202
FS1	0.004	2.046	2.665	0.375	0.284	3.519	0.311	0.011	− 1.123	− 0.381
FS2	0.022	2.004	4.822	0.207	0.170	5.877	0.557	0.186	− 1.208	− 0.242
FS3	0.069	4.938	19.329	0.052	0.170	5.891	1.430	0.823	− 6.023	− 0.309
FS4	0.050	1.119	2.359	0.424	0.494	2.024	0.871	0.118	− 0.248	− 0.087
FS5	0.014	2.625	3.290	0.304	0.239	4.188	0.787	0.084	− 1.700	− 0.482
FS6	0.048	1.702	4.895	0.204	0.101	9.926	0.458	0.429	− 1.030	− 0.206
FS7	0.047	0.813	3.107	0.322	0.334	2.990	0.693	0.164	− 0.032	− 0.009
GS1	0.204	1.715	2.291	0.436	0.476	2.101	6.905	0.508	− 1.008	− 0.364
HS1	0.551	1.712	2.591	0.386	0.502	1.990	23.439	0.765	− 1.011	− 0.327
HS2	0.159	1.673	3.030	0.330	0.470	2.129	5.578	0.501	− 0.909	− 0.260
HS3	0.216	1.664	2.622	0.381	0.481	2.080	8.180	0.554	− 0.867	− 0.279
IS1	0.094	1.515	3.474	0.288	0.240	4.174	1.901	0.489	− 0.825	− 0.222
IS2	0.097	2.256	3.244	0.308	0.288	3.468	2.061	0.444	− 1.975	− 0.559
IS3	0.094	1.981	3.087	0.324	0.280	3.566	1.992	0.430	− 1.745	− 0.518
IS4	0.049	2.555	3.503	0.285	0.246	4.063	0.628	0.224	− 1.774	− 0.473
OS1	0.414	1.722	2.330	0.429	0.286	3.496	10.374	0.776	− 1.217	− 0.465
OS2	0.346	1.990	1.840	0.543	0.461	2.169	9.809	0.611	− 2.569	− 1.116
ZS1	0.286	1.763	2.225	0.450	0.465	2.152	8.281	0.597	− 0.936	− 0.348
ZS2	0.170	1.850	2.466	0.406	0.463	2.161	5.333	0.475	− 1.095	− 0.374

Results of chloro-alkaline indices

Based on the values obtained for chloro-alkaline indices (CA-I and CA-II), all the groundwater samples had negative values of CAI1 and CAI 2 (Table 4). This indicates dominance of direct ion exchange reaction in the research sites. Additionally, the process confirmed that and in groundwater is exchanged with and in the host rock during the contact time of groundwater with the aquifer material^20,56,57. Ige et al.²⁶ also affirmed the prevalence of direct ion exchange reaction via the values of chloro-alkaline indices at the same study area. The dominancy of deionization process in hydrochemistry of the research location is also akin to the study done in Owerri and its environs (Southeast, Nigeria) by⁴.

Interpretation of Piper diagram

The Piper plot (Fig. 6) reveals the hydro geochemical facies of water samples collected within FUNAAB and its environs. From the plot, 100% of samples fall within the (Na⁺ + K⁺) axis, and thus belong to sodium/potassium type, while none of the samples falls under calcium type, magnesium type or “no dominant” type axis. In anion region of the plot, all the points (100%) fall within the bicarbonate axis. It was further discovered from Fig. 6 that 100% of samples have more alkalis than alkaline earth metals and more weak acids (bicarbonates) than strong ones (Cl and SO₄)⁵⁸. In this study, Piper trilinear plot revealed that the dominant hydro geochemical facies in the study locations are mixed and types. The mixed water type () is attributed to water–rock interaction as a result of silicate weathering, simple dissolution process and ion exchange reactions^59,60. The water type of sampled groundwater in the study area could also be suggestive that the dissolved load of the GW in the study site is largely contributed by geogenic source^8,15. Furthermore, the result of water type in the study area reveals that rock-water interaction, ion exchange process and weathering of parent rock influence the quality of groundwater in the study location^16,33.

Fig. 6.

Piper Trilinear diagram of water samples in FUNAAB and its environs.

Water Quality Index (WQI)

The computed WQI was found to range between 12.83 and 58.74% (Table S6). The result obtained revealed that 60% of the groundwater samples fall under the class ‘Excellent’, 36.67% is ‘good’ while the remaining 3.33% falls under the class ‘Poor’ and would thus need treatment. From this result, we can then deduce that approximately 97% of the water samples were apposite for consumption need except sample OS2. The poor category of sample OS2 can be attributed to the high concentration of Na⁺ and K⁺ in the sample relative to others. Thus, water treatment is essential in the groundwater sample OS2²¹. The prevalence of groundwater samples in “good to excellent” category highpoints the fitness of aquifer system in the location for drinking and consumption need while their absence in very poor category designates marginal pollution and advantageous hydrogeological conditions^9,61. The spatial distribution of WQI values, presented in Fig. 7 identifies northwest and southwest parts of the study area with excellent water quality while north east and eastern areas of study location are of good water quality except sample OS2.

Fig. 7.

Spatial distribution map for WQI for the study area.

Results of quality assessment for irrigation purpose

The computed outcomes for irrigation potential index were presented in Table 5. The Na% was found to range from 50.11 to 99.38% with the lowest at HS1 and highest at FS1. None of the samples have %Na under 20%, suggesting that none of the samples was categorized as excellent for irrigation use⁹; a small percentage, 3.3%, of the samples fell within the permissible range (40–60%), which indicates that these few samples could be used for irrigation with a moderate risk of soil deterioration over time. However, majority of the samples, (50%) were classified as doubtful since their Na% values lies between 60 and 80%. This suggests that half of the groundwater samples pose a moderate to high risk of impacting soil permeability, which could eventually hinder agricultural productivity if used for irrigation purposes over the long term^3,47. Moreover, 46.7% of the samples had values of %Na exceeding 80%, categorizing them as unsuitable for spraying. These samples are characterized by high sodium content, which could lead to significant issues with soil structure, reduced aeration and soil permeability, making those samples largely unsuitable for agricultural use^3,9.

Table 5.

Values of irrigation parameters in groundwater samples.

S/code	Na(%)	SSP	SAR	PI	KR	MAR
AS1	68.25	71.43	2.44	144.13	2.15	10.67
AS2	78.25	79.52	2.55	208.65	3.60	27.17
CS1	69.08	71.48	2.60	136.72	2.23	10.20
CS2	91.76	92.16	4.55	237.03	11.14	71.86
CS3	74.37	75.88	2.22	202.06	2.90	23.42
CS4	91.88	92.15	4.24	257.39	11.31	84.40
CS5	79.00	80.94	2.79	185.93	3.76	25.43
CS6	81.95	82.68	3.54	160.00	4.54	22.36
CS7	65.02	70.90	1.88	155.69	1.86	13.18
CS8	80.50	82.83	1.87	335.22	4.13	56.33
CS9	81.81	85.22	2.49	252.35	4.50	42.75
FS1	99.38	99.40	20.86	196.89	160.84	76.28
FS2	94.87	95.32	5.77	249.81	18.48	64.22
FS3	78.69	84.00	2.03	287.23	3.69	41.15
FS4	88.76	89.80	3.94	218.80	7.89	53.45
FS5	98.14	98.19	12.29	189.92	52.68	55.96
FS6	87.61	89.40	2.87	282.10	7.07	68.57
FS7	83.50	86.53	2.32	307.62	5.06	59.08
GS1	75.26	78.08	3.19	142.54	3.04	12.65
HS1	50.11	54.12	1.85	97.41	1.00	4.09
HS2	75.09	77.47	2.88	161.11	3.01	15.20
HS3	71.29	73.59	2.81	142.22	2.48	10.89
IS1	81.21	83.89	2.71	214.67	4.32	34.47
IS2	86.84	89.70	4.27	175.50	6.60	32.67
IS3	86.20	89.64	3.99	181.55	6.25	33.42
IS4	93.26	93.76	6.30	184.50	13.84	61.44
OS1	61.37	67.15	1.99	125.28	1.59	8.79
OS2	71.41	81.75	3.05	121.80	2.50	9.25
ZS1	69.60	71.54	2.58	134.31	2.29	10.77
ZS2	78.80	80.80	3.47	150.31	3.72	15.79

The Soluble Sodium Percentage (SSP) values observed in this study ranged from 54.12 to 99.40, with HS1 exhibiting the lowest SSP value and FS1 the highest (Table 5). This is an indication that all the groundwater samples fall under the category ‘Unsuitable’. This finding further proposes that sodium ions dominates the water chemistry, with a much lower proportion of calcium and magnesium ions. The dominance of sodium cations in the water composition can significantly affect soil productivity, aeration process and permeability over time^3,9. The SAR results (1.85–20.86 meq/l) showed that 93% of groundwater samples fall under the category ‘Excellent’ while sample FS5 was classified as ‘Good’ based on its SAR value (12.29) . However sample FS1 had SAR value greater than 18 and considered as ‘Fair’ for irrigation purpose (Table 5). This means that while FS1 may be used for irrigation in the short term, there is a risk that its use could lead to reduced soil permeability and decreased plant growth over time due to the higher sodium concentration, culminating in reduced crop yields^4,30,47. The Permeability Index (PI) values in this study ranged from 97.41 to 335.22% indicating that all groundwater samples fall under the category ‘Excellent’. The KR estimates ranged from 1.00 to 160.84 which suggests that all the groundwater sample fall under the category ‘Unsuitable’ for irrigation owing to alkali hazards³. This unsuitability indicates that most of the groundwater samples have high sodium content relative to calcium and magnesium. Such an imbalance in ion concentrations can lead to alkali hazards that adversely affect soil permeability, causing it to become compacted and reducing its ability to absorb and retain soil moisture^9,46. The magnesium adsorption ratio (MAR) result in this study range from 4.09 to 84.40% (Table 5). These estimates show that 66.7% of the samples had MAR values less than 50%, signifying that these water samples were suitable for irrigation whereas the remaining 33% of the groundwater sample had value greater than 50%, making them unsuitable for watering purpose. This mixed result suggests that there is noteworthy variance in magnesium levels among the samples. While more than half of the samples are fit for spraying, the higher magnesium concentrations in the remaining samples may present challenges for long-term irrigation. If these waters are used for irrigation over extended periods, they could contribute to soil degradation, water infiltration problems, stunted plant growth culminating in reduced crop yield, especially if magnesium levels are not properly managed^9,44.

Suitability for industrial need

The computed result of the groundwater samples for industrial uses is presented in Table 6. The L-S values for all groundwater sample ranged from 0.06 to 0.79 meq/l with an average of 0.41 meq/l, indicating very low corrosivity risk. These values fall below the threshold of 0.80, which is considered the limit for non-aggressive water. The LSI value ranged between − 3.91 and − 7.53 meq/l (average = − 5.39 meq/l). Based on LSI classification, all the water samples had LSI below zero which signposts that the water are under saturated in terms of CaCO₃ and are highly corrosive but possess low scaling tendency. The RSI computed result ranged from 15.45 to 22.12 (mean = 18.31). If the RSI is more than 6.8, water shows a higher corrosive tendency. Therefore, 100% of the water samples showed an indication of rigorous corrosive tendency based on RSI values. It must be stated that RSI result correlates perfectly with the result obtained for LSI. The PSI measures the scaling potential of water⁶². From the result, PSI values for all samples were below zero, suggesting that the aquifer system in the study locations had very high scaling and corrosive tendency. The CSMR values ranged from 1.99 to 38.56 (average = 5.36). This suggests that 100% of samples are predicted to be corrosive. Therefore, all the groundwater samples are likely to undergo galvanic corrosion with metallic pipe since CSMR values are > 0.5. The AI of all samples varied from 4.89 to 8.54 (average = 6.8). From the result, all groundwater samples have AI less than 10, an indication that the water is severely corrosive, hence unsuitable for industrial purpose.

Table 6.

Results of LSI, RSI, PSI, AI, LS and CSMR of all collected water samples.

S/Code	LSI	RSI	PSI	AI	LS	CSMR
AS1	− 4.82	16.86	− 11.66	7.35	0.51	2.31
AS2	− 5.35	17.88	− 13.67	6.81	0.47	2.32
CS1	− 4.87	16.93	− 11.69	7.30	0.28	38.56
CS2	− 5.98	19.43	− 17.24	6.16	0.30	4.76
CS3	− 5.29	17.76	− 13.41	6.86	0.25	5.64
CS4	− 6.64	20.42	− 18.62	5.49	0.28	4.68
CS5	− 5.48	18.04	− 13.71	6.67	0.37	3.52
CS6	− 5.67	18.21	− 13.69	6.49	0.21	14.68
CS7	− 5.21	17.46	− 12.55	6.94	0.38	4.31
CS8	− 6.13	19.34	− 16.41	5.99	0.30	5.50
CS9	− 5.62	18.48	− 15.04	6.51	0.25	6.56
FS1	− 7.53	22.12	− 21.78	4.61	0.48	3.52
FS2	− 6.78	20.33	− 17.72	5.34	0.24	5.88
FS3	− 6.04	18.88	− 14.94	6.10	0.06	5.89
FS4	− 6.25	19.31	− 15.77	5.90	0.63	2.02
FS5	− 6.79	20.60	− 18.69	5.34	0.38	4.19
FS6	− 6.59	20.07	− 17.46	5.52	0.22	9.92
FS7	− 6.06	19.23	− 16.28	6.06	0.43	2.99
GS1	− 4.70	16.83	− 12.04	7.46	0.64	2.10
HS1	− 3.91	15.45	− 9.73	8.26	0.58	1.99
HS2	− 4.70	16.88	− 12.21	7.46	0.48	2.13
HS3	− 4.49	16.50	− 11.55	7.68	0.56	2.08
IS1	− 5.63	18.41	− 14.55	6.56	0.36	4.17
IS2	− 5.42	18.15	− 14.36	6.76	0.40	3.47
IS3	− 5.49	18.21	− 14.39	6.66	0.41	3.57
IS4	− 6.01	19.27	− 16.50	6.14	0.36	4.06
OS1	− 5.03	17.12	− 11.84	7.13	0.55	3.50
OS2	− 4.99	17.11	− 11.93	7.18	0.79	2.17
ZS1	− 4.83	16.98	− 12.09	7.33	0.66	2.15
ZS2	− 4.83	17.09	− 12.56	7.33	0.59	2.16

Correlation analysis

Table S7 presents the correlation coefficient matrix between and among measured physicochemical parameters of groundwater samples. Statistically significant positive relationship was established between EC and TDS (0.691) as well as pH versus EC/TDS (0.526). Furthermore, significant direct correlation exists between EC and each of Cl^- (0.772) and (0.716) at p < 0.01 level. This concurs with moderate correlation between EC versus TDS reported by⁷. Moderate direct relationship between EC and TDS proposes that electrical conductivity is swayed by the levels of hydrogeochemical processes and anthropogenic pollution⁹. Direct correlation between EC and each of Cl^- and indicates likelihood of localized impact of nearby anthropogenic inputs in the nearest future. Moderate correlation exists between TDS and each of Ca²⁺ and Na⁺ at p < 0.01 level of significance. Inverse relationships occurred between turbidity and each of pH, EC as well as TDS of groundwater samples. However, turbidity exhibits strong positive relationship with Mg²⁺ (r = 0.719). Positive correlation between Mg²⁺ and turbidity suggests possible leaching of Mg-rich minerals in sediment and suspended particulates of groundwater systems in the study locations. Similar direct relationship between Mg²⁺ and turbidity in groundwater samples was also reported by⁶³. Nitrate exhibits moderate direct association with pH, EC, and Na⁺ (r = 0.530, 0.688, 0.529 &0.578, respectively at 1% level. In addition, moderate associations occurred between and each of Na⁺ and Ca²⁺. However, nitrate exhibits strong direct association with TDS (r = 0.895, p < 0.01). Akakuru et al.⁴ also reported direct relationship between nitrate and pH in groundwater samples. Moderate correlation between nitrate and Na⁺ (r = 0.578) suggests that untreated sewage discharge has potential to contributes moderately to Na⁺ stuffing into the aquifer units²⁶.

Additionally, moderate direct associations between nitrate and each of Na⁺ and Ca²⁺ could be an indication of little influence of nearby human-origin inputs on the chemistry of aquifer system in the research location at present¹⁴. It was observed that has weak relationships with (0.428), with K⁺ (0.341) and with Mg²⁺ (0.277). Weak correlations between nitrate and each of and K⁺ also implies little impact of agricultural inputs on hydrochemistry of the research location²⁶. From Table S7, chloride exhibits modest direct association with pH (r = 0.620), TDS (r = 0.525) but strong correlation with EC (r = 0.772). However, exhibits weak positive correlation with (r = 0.392). According to⁹, moderate positive association between and pH suggests possible anthropogenic influence. However, weak association between and indicates chloride ion source was from atmospheric depositions like rainfall⁶⁴. Sodium ions exhibiting positive correlation with TDS (r = 0.610), with EC (r = 0.899) and with Ca²⁺ (r = 0.602) revealed an alkalinizing impact on groundwater system (as evidenced by pH > 7.0 in 83.3% of total samples). These correlations further suggest that water–rock interaction is a potential significant contributor to the quality of groundwater samples in the research locations^47,65.

However, moderate correlations between Na⁺ and Cl^- (r = 0.695), Na⁺ versus (r = 0.606) and Na⁺ versus (0.578) at 1% level indicate likely influence of agricultural inputs on groundwater system⁷. Weak direct association exists between K⁺ and Na⁺ (r = − 0.439). This portrays predominance of direct ion exchange process as major influencer of groundwater chemistry at the investigated locations¹⁴. K⁺ exhibiting moderate direct association with EC (r = 0.518) suggests its possible source as K-bearing minerals from underlying lithology²⁶. However, likely K⁺ loading from anthropogenic source is evidenced by weak association between K⁺ and (r = − 0.341) and K⁺ and Na⁺ (r = − 0.439)²⁶.

Principal component analysis

The reliability analysis for PCA shows that the variables are sufficiently correlated and have enough common variance for factor analysis. The Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy is 0.645 while the Bartlett’s test of sphericity is 368.469 at p < 0.05. The results of PCA using varimax rotation method revealed four (4) principal components having their eigenvalues greater than unity and contributed a total of 79.94% of the total variance in the data set. (Table 7). Principal component I accounts for 43.88% of the total variance and is characterized by strong positive loadings on pH, TDS, EC, ,, , Ca²⁺ and Na⁺. However, negative and weak positive loadings characterized the remaining parameters in PC1. Parameters in PC1 with strong positive loadings reflect water–rock reaction within the aquifer system, thus suggesting a common geogenic source^7,26. Furthermore, all these ions with strong positive loadings in PC1 suggests that groundwater in the study area is replenished with freshwater which later interacts with the soil carbon dioxide to form ⁷. The strong positive loading of nitrate and sulphate in PC1 could be an indication of nearby agricultural practices and drainage system in some of the water sampling points¹⁹. Principal component 2 (PC2) has strong positive loadings on carbonate and bicarbonate ions but negative weak loadings on , Na⁺, K⁺, EC and TDS. Strong loadings on bicarbonate and carbonate ions suggest possible common lithogenic source and aligns with positive correlation between the pair as shown in Pearson correlation Table S7. Significant loading of suggests weathering of silicate minerals could be the primary source of the weak anions in the studied groundwater system¹⁹. Principal component 3 accounted for 12.83% of the entire variance in the data and characterized by robust positive loading on turbidity (0.925), strong negative loading on Mg²⁺(− 0.799) and weak loadings on the remaining parameters. This resembles the outcomes of correlation analysis where Mg²⁺ exhibits positive correlation with only turbidity. PC4 accounted for 7.66% of the overall variation and has robust positive loading only on dissolved oxygen (DO) (0.920). This probably suggests that factors influencing DO levels are operating distinctly from the factors imparting other analyzed physicochemical parameters of studied groundwater samples⁶⁶. This means that since the PCA explained 79.94% of the entire variance in the data, the unexplained 20.06% perhaps suggested the contribution from other unconfirmed parameters which could impact the worth of aquifer system in the investigated locations²⁶. Therefore, further studies are recommended.

Table 7.

Component loading eigenvalues and variance of mined constituents.

Parameters	Component1	Component 2	Component 3	Component 4
pH	0.711	0.339	0.003	0.315
TDS	0.749	− 0.379	− 0.089	0.095
EC	0.924	− 0.181	0.066	0.016
turbidity	− 0.103	0.001	0.925	0.102
DO	− 0.288	0.153	− 0.008	0.920
	0.484	0.806	− 0.099	0.069
	0.859	0.064	0.282	− 0.033
	0.825	0.146	0.228	− 0.094
	0.800	− 0.223	− 0.121	− 0.030
	0.811	0.011	− 0.043	− 0.107
	0.481	0.040	− 0.799	0.105
	0.794	− 0.199	0.346	0.138
K+	0.465	− 0.597	− 0.108	0.109
Initial eigenvalue	6.144	2.178	1.797	1.072
% of variance	43.888	15.560	12.834	7.656
Cumulative %	43.888	59.448	72.281	79.937

Cluster analysis results

According to hierarchical cluster analysis based on water sampling points, four groups were identified (Fig. 8a). Cluster 1 has 10 sampling points (CS5, IS3, CS6, IS4, FS4, AS2, CS3, CS7, FS5 and FS1) that represents 33.33% of total sampling points which have similar chemical properties (In this case, EC > 150 µS/cm, but less than 250 µS/cm). These samples are mostly likely impacted by geogenic source, natural recharge and limited human interference^5,20. Cluster 2 has 8 samples (FS7, FS6, CS8, CS4, CS2, FS3, FS2, and CS9) representing 26.67% of total samples. The water samples of this cluster are characterized by TDS < 80 mg/l, EC < 150 µS/cm, nitrate less than 2 mg/l and calcium ions of less than 2 mg/l, suggesting the water system in this cluster is affected by rock-water interaction. Cluster 3 contains only two samples (IS1 and 1S2) that had similar physico-chemical properties such as pH above 7.0, DO above WHO acceptable threshold of 5 mg/l, TDS > 200mg/l and nitrate content of approximately 3 mg/l, indicating water likely to be affected by human activities in the nearest future.

Fig. 8.

(a) Dendrogram of groundwater sampling locations. (b) Dendrogram of tested physicochemical parameters in groundwater samples.

Cluster 4 has 10 samples (OS1, OS2, HS1, HS2, HS3, GS1, ZS1, AS1, ZS2 and CS1) constituting 33.33% of the total samples. The water of ten samples of Cluster 4 have similar properties such as TDS < 200 mg/l, pH above 7.00, EC > 250 µS/cm, Cl^- greater than 20 mg/l and 2 mg/l < nitrate < 3 mg/l, suggesting waters that tend to demonstrates potential impact of nearby human activities in the nearest future. This cluster shows higher dissolved ionic concentration in terms of EC than the remaining clusters based on sampling points.

Dendrogram based on analyzed physicochemical parameters identified three (3) clusters (Fig. 8b). Cluster 1 contains only EC and reveals parameter with the highest positive loading (0.9240) amongst the principal components, indicating that EC is regulated by ecological influences such as mixing of ions through rock-groundwater synergy⁷. Cluster 2 contains TDS and bicarbonate ions, indicating the influence of soil carbon dioxide on TDS concentration²⁰. Cluster 2 that contains TDS and bicarbonate ions suggest that intensive farming will elevate the basicity due to bicarbonate ions⁷. Cluster 3 contains Na⁺, Cl^-, K⁺, , Ca²⁺, pH , DO, turbidity, Mg²⁺ and .This cluster possibly suggests contribution from geogenic/lithogenic sources.

Conclusions

The study examines the quality and hydrogeochemical characteristics of groundwater sources within FUNAAB and its environs using hydrochemical, hydrogeochemical, indexical approach and multivariate statistics. Hydrochemical data of groundwater samples revealed that the groundwater system in the study area was neutral/slightly alkaline in nature. According to WHO permissible thresholds for drinking water, the concentrations of most analyzed physicochemical properties in sampled groundwater were within the allowable limits, thus fit for drinking purpose. The average abundance order of main cations and anions are and , respectively. The Piper trilinear plot revealed that the predominant water types in the study region are and mixed . Ionic ratios and CAI suggest the geochemical processes that affect the groundwater’s chemistry there include silicate weathering, direct ion exchange and little localized anthropogenic inputs. According to the WQI assessment, 97% of total samples were of “good to excellent” rating and thus suitable for drinking. With the exception of PI, SAR and MAR effect, practically all groundwater samples are safe and appropriate for irrigation use based on all accepted IPI. Mean values of LSI, RSI, AI and CSMR suggest high corrosivity tendency in the collected groundwater samples while PSI and L-S values inferred scaling potential of tested water samples. Generally, the groundwater quality evaluation proposes that the majority of sampled water is potable and appropriate for irrigation use with little treatment. Furthermore, the use of corrosion inhibitors in the groundwater systems of the study locations should be advocated.

Author contributions

All authors contribute to the study conception and design. Material preparation, data collection, analyses and Interpretation were performed by all the authors. Saheed Adekunle Ganiyu, Olamilekan Thompson Bamisebi, Boluwatife Daniel Omole, Babatunde Sodiq Arowolaje, Mubarak Abiodun Adeyemi and Hakeem Iyiola Kuforiji : Conceptualisation, Methodology, Investigation, Formal analysis, Visualisation,—original draft. Saheed Adekunle Ganiyu-Writing—review & editing, Nadeem A Khan: review & editing. Roohul Abad Khan, Hakeem Iyiola Kuforiji, Nadeem A Khan: Software, Supervision, Data curation, Validation, Writing—review & editing. Saheed Adekunle Ganiyu: Software, Formal analysis.

Funding

No fund was received for conducting this study.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.