Assessment of Groundwater quality for drinking water purposes in Sub-Saharan Africa environment: the case study of Ebolowa City Council, Cameroon (Central Africa)

doi:10.21203/rs.3.rs-5129039/v1

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Assessment of Groundwater quality for drinking water purposes in Sub-Saharan Africa environment: the case study of Ebolowa City Council, Cameroon (Central Africa)

https://doi.org/10.21203/rs.3.rs-5129039/v1

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The present study was carried out to evaluate the groundwater quality and its suitability for domestic purposes in the Ebolowa City Council (ECC). The groundwater quality in ECC has been evaluated based on the Water Quality Index (WQI). A total of 15 groundwater samples were collected, and their physical parameters (temperature, pH, EC, TDS, and TSS) and microbial content (fecal coliforms, fecal streptococci, and Total Coliforms) were analyzed using standard methods. The results indicated that the physical characteristics of the water (temperature range from 24°C to 30 °C; pH range from 3.7 to 5.6; EC range from 114 μS/cm to 1,818 μS/cm; TDS range from 54 mg/L to 913 mg/L; TSS range from 0 mg/L to 24 mg/L) were within WHO guidelines for potability except for the temperature, EC, and TSS. The chemical characteristics of groundwater (NO₃^- range from 0 mg/L to 19.8 mg/L; NH₄⁺ range from 0.2 mg/L to 12.9 mg/L) were also within WHO guidelines for potability, except for NH₄⁺. The fecal Coliforms ranged from 1 to 51 CFU/100 ml, while the fecal streptococci ranged between 0 and 25 CFU/100 ml. The concentration of Total Coliform is between 2.0 and 84.0 CFU/100 ml. The groundwater quality index reveals that ten samples out of fifteen have water unfit for consumption, three are very poor, and one is poor.

Environmental Engineering

Drinking water

Groundwater

Water quality index.

The study evaluates the groundwater quality and its suitability for domestic purposes in the Ebolowa city council (south region of Cameroon).
The groundwater quality index reveals that ten samples out of fifteen have water unfit for consumption.

Good-quality water is essential for human survival, well-being, food production, and socioeconomic development. It is typically derived from two main natural sources: surface water and groundwater (Boateng et al., 2016). Biological and chemical contaminants originating from point and non-point sources have the potential to pollute both surface and groundwater supplies (Rohul-Amin et al. 2012). Therefore, access to safe drinking water is a major issue in developing countries, especially in sub-Saharan Africa (Mvongo and Defo, 2021).

Because of the extraordinary growth in population and the rapid urbanization over the past three decades, there has been a notable impact of man on the environment. Groundwater in particular has been continuously and gradually degraded as a result of this. Diseases are spread largely through contaminated water (Adelagun et al., 2021). Children continue to be affected by diseases that are fully preventable due to unsafe water, sanitation, and hygiene. Over 1,000 of the over 4,000 daily deaths from diseases linked to poor WASH are children under the age of five (UNICEF, 2023).

Numerous studies (Ameen, 2019; Golaki et al., 2022; Ram et al., 2021; Tontsa et al., 2023; Unigwe and Egbueri, 2023) have examined physicochemical and bacteriological factors to evaluate the properties of groundwater. Groundwater pollution has increased as a result of surface contamination brought on by population growth, urbanization, and industrialization, particularly when people are drawing water from shallow, unconfined aquifers (Lapworth et al., 2017; An et al., 2023). Sewage discharge, industrial and agricultural waste, both organic and inorganic waste, mining, fertilizers, and pesticides that are washed off the land by rain are the most frequent sources of groundwater pollution (Isiuku and Enyoh, 2020; Ma et al., 2023).

Since most of the surface waters are polluted by human activities, the majority of these people rely on groundwater by drilling boreholes and hand-dug wells for their sustenance (Mvongo et al., 2023). Ebolowa is one of those urban areas that still has some deficit with respect to water coverage and relies solely on hand-dug wells and boreholes. The present study was carried out to evaluate the groundwater quality and its suitability for domestic purposes in the Ebolowa city council (south region of Cameroon).

The evaluation of water quality is crucial for aquatic life as well as human health. Water quality greatly affects water supply and frequently impacts available supply options (Adelagun et al., 2021). Given the rising per capita water demand and the ongoing loss in freshwater accessibility, it is crucial for society, the economy, and conservation efforts to understand and monitor the sources and quality of the water utilized for water delivery (Githaiga et al., 2021; Yin et al., 2021). The quality of the local water can be utilized to determine the origins and final destinations of harmful pollutants and contaminants that come from the local ecology, geology, and anthropogenic activities.

2.1. Study area

Ebolowa City Council is built on the southern plateau of Cameroon, in a somewhat rugged valley surrounded by green hills (Fig. 1). It is subject to an equatorial climate of the Guinean type with four seasons: two rainy seasons separated by a short dry season (from July to August) and a long dry season that extends from December to February. The average interannual precipitation is around 1750 mm (Mvongo et al., 2022a). The average annual value of insolation is between 1500 and 1750 hours (Mvongo et al., 2022b). Air temperatures are high and vary little throughout the year. The average temperature value is 23.5°C (Mvongo et al., 2022a).

The soil cover consists of ferralitic and hydromorphic soils found in marshy areas. The town of Ebolowa is located in the watershed of the Mvila, the main river in the region. Its hydrographic network is made up of several rivers whose major flow directions are north-east to south-west. Among these rivers, we distinguish outside the Mvila: Mfiande, Mfoumou, Bengo’o, and Seng. Demographically, the population of the city of Ebolowa is estimated at 96,495 inhabitants (Ebolowa City Council, 2015). This population is distributed in twenty-six (26) districts that make up the city, of which the most populated are: Angalé, Ebolowa-Si 1, Ebolowa-Si 2, Abang 1, Abang 2, Nko’ovos 1, Nko’ovos 2, and Mekalat Yevol.

2.2. Data collection

2.2.1. Secondary data

Secondary information was obtained from the database of the Participatory Development Aid Software (PRO-ADP) of the Ebolowa I and II councils, diagnostic reports of the Urban Master Plan of the city of Ebolowa, and land use plans of the Ebolowa I and II councils. Specifically, the data collected in these documents related to groundwater catchment works built in the city of Ebolowa, water uses, and groundwater pollution factors.

2.2.2. Primary data

Water samples were collected in 0.33 liter plastic bottles previously sterilized in the laboratory and then rinsed three times with sample water at the site before sampling. Water from undeveloped wells was collected in containers for common use by residents before being transferred to bottles intended for collection. As for water from springs, wells, and boreholes, the samples were taken directly with the sampling bottles. The water samples taken were stored directly in a cooler containing dry ice from the sampling location at the laboratory for analysis.

A total of 15 water samples were taken, of which six came from developed wells, five from undeveloped wells, three from springs, and one from a borehole. They were sent to the laboratory for analysis. Twelve parameters were analyzed, including temperature, pH, redox potential, salinity, electrical conductivity, total dissolved solids, total suspended solids, nitrates, ammonium, fecal coliforms, fecal streptococci, and total coliforms. Table 1 presents the methods used to analyze each parameter.

Table 1

Methods used to analyse parameters
Parameters	Abbreviation	Units	Methods of analysis
Temperature	T	°C	Electrochemical
pH	pH	-	Electrochemical
Electrical Conductivity	EC	µS/cm	Electrochemical
Total Dissolved Solids	TDS	mg/l	Electrochemical
Total Suspended Solids	TSS	mg/l	Colorimetry by UV spectrometry
Nitrate	NO₃^-	mg/l	Colorimetry by UV spectrometry
Ammonia	NH₄⁺	mg/l	Colorimetry by UV spectrometry
Faecal Coliforms	FC	UFC/100ml	Membrane filtration
Faecal Streptococci	FS	UFC/100ml	Membrane filtration
Total Coliforms	TC	UFC/100ml	Membrane filtration

2.3. Data analysis and processing

2.3.1. Statistical analysis and spatial distribution pattern

Statistical data was processed using Microsoft Office Excel and Rstudio software. Basic statistics such as the mean and standard deviation were calculated. The Pearson correlation matrix was also used to identify the relationship between different water quality parameters. The inverse distance Weighted (IDW) interpolation technique was used in this study for spatial interpolation of groundwater quality parameters, leading to the generation of spatial interpolation of groundwater quality parameters. The IDW is now an excellent method for groundwater spatial interpolation (Sarfo and Shankar, 2020). Weights were allocated to various criteria based on distance at each place and calculated, taking into account the nearest specified locations. The distribution of each groundwater quality indicator has been delimited in separate zones on a spatial distribution map, namely acceptable, desirable, and permissible limits for drinking purposes, according to WHO (2017).

2.3.2. Calculation of Water Quality Index

The water quality index (WQI) is considered a powerful tool that can present a comprehensive picture of groundwater quality. The WQI is the rate that reflects the integrated impact of different water quality variables (Al-Mashagbah, 2015). The WQI was calculated as follows: each parameter was assigned different weights (w_i) on a scale of 1 (least effect on water quality) to 5 (highest effect on water quality) based on their perceived effects on primary health and according to their relative importance in drinking water quality. The highest weight of 5 was assigned to parameters that have critical health effects and whose presence above the critical concentration limits could limit the usability of the resource for domestic and drinking purposes (NO₃⁻, NH₄⁺, FC, FS, and TC). The minimum weight of 1 was assigned to temperature because of its insignificant role in water quality assessment. Other parameters, such as pH, EC, TSS, and TDS, were assigned weights between 2 and 4 based on their relative significance in the water quality evaluation. The relative weight (W_i) is computed from the following equation:

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

Where, W_i is the relative weight, w_i is the weight of each parameter, and n is the number of parameters. The calculated relative weight (Wi) values of each parameter are given in Table 2.

Table 2

Relative weight of water quality parameters
Parameters	Unit	WHO standards	Weight (w_i)	Relative weight (W_i)
T	°C	25	1	0.025
pH	-	6.5–8.5	4	0.100
EC	µS/cm	1,400	4	0.100
TDS	mg/l	500	2	0.050
TSS	mg/l	20–24	2	0.050
NO₃⁻	mg/l	50	5	0.125
NH₄⁺	mg/l	0.5	5	0.125
FC	CFU/100 ml	0	5	0.125
FS	CFU/100 ml	0	5	0.125
TC	CFU/100 ml	0	5	0.125
Total			40	1.000

The quality rating (q_i) for each parameter is assigned by dividing its concentration in each water sample by its limit values given by the WHO (2011) and multiplying the result by 100.

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

where, $\:{q}_{i}$ is the quality rating, $\:{C}_{i}$ is the concentration of each parameter in each water sample, and $\:{S}_{i}$ is the drinking water standard for each parameter according to the WHO standards (WHO, 2011). To calculate WQI, the SIi value should be determined with the following equations:

$$\:{SI}_{i}={W}_{i}\times\:{q}_{i}$$

$$\:WQI=\sum\:_{i=1}^{n}SI$$

where, $\:{SI}_{i}$ is the sub-index of ith parameter; $\:{q}_{i}$ is the quality rating based on concentration of ith parameter (Ramakrishnaiah et al., 2009). The computed WQI values are classified into five categories as follows (Table 3).

Table 3

The WQI categories
Range	Quality
< 50	Excellent
50–100	Good
100–200	Poor
200–300	Very poor
> 300	Unsuitable for drinking
Source: Batabyal and Chakraborty (2015)

3.1. Groundwater quality parameters and spatial distribution pattern

Table 5 presents the results of physicochemical and bacteriological analyses of groundwater in the city of Ebolowa. Table 5 shows that the temperature values oscillate between 24°C and 30°C, with an average value of 25.5°C. They are mostly above the WHO guideline value of 25°C. These differences can be explained by the fluctuations recorded by the ambient temperature during the sampling as well as the various activities that develop around the sampling points.

Analysis of the data in Table 5 shows that all the water samples taken are acidic, with a pH between 3.7 and 5.6. This result implies positive values of the redox potential, which indicates the presence of strong oxidants with redox potential values between 70.2 mV and 179.5 mV. In addition, salinity is generally low, with values between 0.1‰ and 0.9‰. These values are consistent with the natural and geological environment of the center-south zone of Cameroon, where the superficial aquifer, depleted of basic cations, is recharged by rainwater, itself already acidic (Defo et al., 2016; Ewodo et al., 2016).

Table 5 also shows that 87% of the water samples analyzed presented conductivity values between 114 µS/cm and 1,818 µS/cm with an average value of 629.2 µS/cm. These waters therefore have low- to medium-level mineralization. With regard to TDS, the concentrations of this parameter vary from 169 to 913 mg/l in modern wells, from 189 to 559 mg/l in traditional wells, and from 54 to 351 mg/l in springs and boreholes. In addition, 47% of the samples analyzed have TSS concentrations that do not comply with WHO recommendations. Modern water points (Boreholes and modern wells) seem to be less exposed to TSS pollution than other types of structures.

Nitrate (NO₃⁻) concentrations are not high, with values between 0 and 19.8 mg/l. These values are below the threshold value recommended by the WHO (50 mg/l). Nitrates are the main forms of nitrogen in waters and can be used as indicators of chemical pollution of waters. Fagbayide and Abulude (2018) link the presence of nitrates in waters, in addition to the normal nitrogen cycle, to different sources, namely: organic and inorganic chemical fertilizers, pesticides and herbicides, animal breeding facilities, and domestic and industrial effluents.

The concentrations of ammonium ions (NH₄⁺) are between 0.2 and 12.9 mg/l, with an average value of 1.5 mg/l. About 40% of the water samples showed NH₄⁺ concentrations above the limit value recommended by the WHO (0.5 mg/l). Of these, 50% come from modern wells, 17% from traditional wells, and 33% from springs. These high NH₄⁺ values show proximity to the source of contamination through urine and feces due to the proximity of the toilets.

The FC concentration is between 1 and 51 CFU/100 ml, with an average value of 11.3 CFU/100 ml. The concentration of FS is between 0 and 25 CFU/100 ml, with an average value of 6.1 CFU/100 ml. The concentration of TC is between 2.0 and 84.0 CFU/100 ml, with an average value of 24.1 CFU/100 ml. In addition, all the samples analyzed showed the presence of germs, indicating fecal pollution. Indeed, the level of sanitation in the study area is very precarious with regard to waste management, particularly wastewater and latrines. The vast majority of excreta is stored in bottomless latrines, the pit of which generally reaches the water table and constitutes a risk of microbiological contamination of groundwater through the process of diffusion of contaminants in the soil.

3.2. Spatial distribution pattern

The spatial distribution pattern of the contour maps of the groundwater quality parameters has been generated, as represented in Fig. 2. The temperature distribution diagram (Fig. 2a) shows that groundwater in the city is generally above 25°C in the northern part and below 25°C in the southern part of the city. The spatial distribution pattern of pH (Fig. 2b) indicates that the northern part of the city has strongly acidic groundwater (pH < 4.5), while in the southern part it is moderately acidic (4.5 < pH < 5.5), with some spots where the water is strongly acidic. The north-central part of the town of Ebolowa has a high redox potential (Fig. 2c). The electrical conductivity is mainly highest (> 1000 µS/cm) in the central part north of the municipal lake (Fig. 2e). Similarly, the salinity is mainly highest in the central part, north of the municipal lake (Fig. 2d). The central part of the city, especially north of the municipal lake, has the highest TDS (> 750 mg/l) in groundwater (Fig. 2f) due to low flow and highly weathered rock formations.

The diagram of the spatial distribution of TSS (Fig. 2g) indicates that the northern part and the southwestern part of the city have the highest concentration of TSS. With regard to nitrate (Fig. 2h), it is generally low, with, however, two areas of high concentration in the center-north part of the city. Another quality parameter is ammonium (Fig. 2i), which shows its presence beyond the authorized limit. The area of high ammonium concentration is observed upstream of the municipal lake in the north-central area of the city. Fecal coliforms (Fig. 2j) are generally present in all groundwater in the city, with a high concentration (> 40 CFU/100 ml) in the northern part of the city. The spatial distribution of FS (Fig. 2k) is similar to that of FC, with an average presence of FS in the southeastern part of the city. On the other hand, the spatial distribution of TC (Fig. 2l) shows the highest concentrations in the northern part and in the southern part. The central area in which the municipal lake is located has the lowest concentrations.

Figure 2. Spatial distribution of temperature, pH, redox potential, salinity, electrical conductivity, TDS, TSS, Nitrate, Ammonium, FC, FS and TC

3.3. Correlation matrix

Table 4 present the correlation matrix between water quality parameters.

Table 4

Pearson correlation matrix between contamination indicator parameters
	TSS	NO₃⁻	NH₄⁺	FC	FS	TC
TSS	1
NO₃⁻	0.537	1
NH₄⁺	-0.158	0.013	1
FC	0.346	0.087	-0.184	1
FS	0.645	0.370	-0.215	0.875	1
TC	0.001	0.048	-0.220	0.759	0.608	1
In bold, significant values (> 0.5)

Table 4 reveals three outstanding patterns. Firstly, a positive and strong correlation exists between fecal coliforms, fecal streptococci (0.875), and total coliforms (0.759). Faecal coliforms are positively and strongly correlated with total coliforms (0.759), and fecal streptococci are positively and strongly correlated with total coliforms (0.608). This suggests that the bacteriological contamination of the groundwater is mainly fecal. Total coliforms may also indicate the presence of additional bacteria that can cause waterborne infections such as typhoid fever, hepatitis, gastroenteritis, and dysentery (Lawson, 2011). As a result, the presence of coliforms in contaminated water makes the water unsafe for human consumption unless chlorinated.

Secondly, the correlation matrix shows the existence of a positive, although less pronounced, correlation between TSS and NO₃⁻ and fecal streptococci. The correlation between TSS and NO₃⁻ is positive and strong (0.537). This suggests that the nitrates present in the water come from the decomposition of the organic matter contained in the TSS. NO₃⁻ is the result of denitrification of NH₄⁺ present in the water, which is oxidized to nitrite by bacteria of the genus Nitrosomonas and then to nitrate by bacteria of the genus Nitrobacter. The correlation between TSS and fecal streptococci is positive and strong (0.645). The correlation between TSS and NO₃⁻ is positive and strong (0.537). This suggests that fertilizers are not only responsible for nitrate enrichment. Finally, a negative and weak correlation exists between bacteria content (faecal coliforms, fecal streptococci, and total coliforms) and nitrogen (respectively 0.087, 0.370, and 0.048 with NO₃⁻ and − 0.184, − 0.215, and − 0.220 with NH₄⁺) concentrations, showing heterogeneity between bacterial and chemical contamination.

Table 5

Concentration of contamination indicators in water samples
Samples name	Sample source	T (°C)	pH	Eh (mV)	Sal (‰)	EC (µS/cm)	TDS (mg/l)	TSS (mg/l)	NO₃⁻ (mg/l)	NH₄⁺ (mg/l)	FC (CFU/100ml)	FS (CFU/100ml)	TC (CFU/100ml)
PA1	Modern well	26.3	4.8	115.6	0.2	380	182.9	0	0	0.3	3	1	2
PA2	Modern well	25.8	4.9	109.6	0.2	327	156.9	0	7	0.4	5	2	9
PA3	Modern well	25.7	5.0	103.9	0.2	352	169.2	0	6	0.5	7	9	14
PA4	Modern well	25.8	4.9	113.1	0.9	1,818	913	0	8.3	12.9	3	1	6
PA5	Modern well	25.7	5.4	81.7	0.3	523	253	24	19.8	0.4	29	25	28
PA6	Modern well	25.7	4.6	127.4	0.6	1,131	559	0	4.5	3.6	14	6	28
P1	Traditional Well	25.4	3.7	179.5	0.6	1,131	559	3	0	2.0	1	0	9
P2	Traditional Well	25.3	4.0	163.0	0.2	474	231	2	0	0.3	51	20	84
P3	Traditional Well	24.9	5.6	70.2	0.3	114	374	5	10.9	0.3	2	0	7
P4	Traditional Well	24.4	4.0	159.9	0.1	987	189.1	0	3.8	0.2	7	3	18
P5	Traditional Well	24.6	4.4	136.1	0.2	393	198.1	0	9.3	0.2	10	7	75
S1	Spring	24.4	4.7	123.8	0.3	531	257	3	0	0.4	5	2	9
S2	Spring	24.1	4.2	147.3	0.2	355	170.6	0	11.7	0.8	17	9	33
S3	Spring	24.0	4.3	142.9	0.4	717	351	1	16.5	0.5	9	4	24
F	Borehole	29.9	4.0	160.8	0.1	114.3	54	4	5.2	0.2	7	3	16
Mean		25.5	4.6	129.0	0.3	629.2	307.9	2.8	6.9	1.5	11.3	6.1	24.1
Median		25.4	4.6	127.4	0.2	474.0	231.0	0.0	6.0	0.4	7.0	3.0	16.0
SD		1.4	0.5	30.9	0.2	462.0	219.9	6.1	6.1	3.3	13.1	7.3	24.3
Min		24.0	3.7	70.2	0.1	114.0	54.0	0.0	0.0	0.2	1.0	0.0	2.0
Max		29.9	5.6	179.5	0.9	1,818.0	913.0	24.0	19.8	12.9	51.0	25.0	84.0
WHO standards		25	6.5-9	-	-	100–1000	‹ 1500	0	50	0.5	0	0	0

CFU Colony forming units, WHO World Health Organization, SD standard deviation, Min minimum, Max maximum

3.4. Water quality index

Table 6 presents the summary of the results on the WQI of the city of Ebolowa, while Fig. 3 presents the spatial distribution of the WQI. Overall, Table 6 shows that ten samples out of fifteen have water unfit for consumption, three samples are very poor, and one sample is poor. Only a yardstick of good quality.

Table 6

Water quality index and its quality class
Sample name	Sample source	WQI Value	Class
PA1	Modern well	89.0	Good
PA2	Modern well	211.8	Very poor
PA3	Modern well	311.4	Unsuitable for drinking
PA4	Modern well	498.3	Unsuitable for drinking
PA5	Modern well	805.0	Unsuitable for drinking
PA6	Modern well	678.7	Unsuitable for drinking
P1	Traditional Well	209.9	Very poor
P2	Traditional Well	1 812.8	Unsuitable for drinking
P3	Traditional Well	145.0	Poor
P4	Traditional Well	357.1	Unsuitable for drinking
P5	Traditional Well	1 145.0	Unsuitable for drinking
S1	Spring	213.4	Very poor
S2	Spring	701.2	Unsuitable for drinking
S3	Spring	473.7	Unsuitable for drinking
F	Borehole	322.0	Unsuitable for drinking

Figure 3 shows that there is a gradual variation in groundwater quality from good to poor quality from the central part of the city (around the municipal lake) towards the south of the city and towards the north of the city.

Groundwater quality and its suitability for drinking purposes in Ebolowa City Council have been evaluated. Results reveal that the groundwater is slightly acidic in nature. The analysis showed that the physical and chemical characteristics of the water (temperature range 24°C–30°C; pH range 3.7–5.6; EC range 114 µS/cm–1,818 µS/cm; TDS range 54 mg/L–913 mg/L; TSS range 0 mg/L–24 mg/L; NO₃⁻ range 0 mg/L–19.8 mg/L; NH4 + range 0.2 mg/L–12.9 mg/L) were within WHO guidelines for potability except for the temperature, EC, TSS, and NH₄⁺. The finding also suggests that the bacteriological contamination of the groundwater is mainly fecal. The nitrates present in the water come from the decomposition of the organic matter contained in the TSS. The groundwater quality index reveals that ten samples out of fifteen have water unfit for consumption, three are very poor, and one is poor. This study provides a baseline for the groundwater quality in Ebolowa City Council, which will help policymakers focus on the specific contaminant sources and their mitigation.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

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The authors declare no competing interests.

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Assessment of Groundwater quality for drinking water purposes in Sub-Saharan Africa environment: the case study of Ebolowa City Council, Cameroon (Central Africa)

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Abstract

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HIGHLIGHTS

1. INTRODUCTION

2. MATERIALS AND METHODS

2.1. Study area

2.2. Data collection

2.2.1. Secondary data

2.2.2. Primary data

2.3. Data analysis and processing

2.3.1. Statistical analysis and spatial distribution pattern

2.3.2. Calculation of Water Quality Index

3. RESULTS AND DISCUSSION

3.1. Groundwater quality parameters and spatial distribution pattern

3.2. Spatial distribution pattern

3.3. Correlation matrix

3.4. Water quality index

4. CONCLUSION

Declarations

CONFLICT OF INTEREST

DATA AVAILABILITY STATEMENT

References

Additional Declarations

Supplementary Files

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