Assessment of groundwater quality for drinking using the water quality index

Access to safe and clean water is fundamental for human well-being and development and is recognized as a basic human right (U.N. Resolution A/RES/64/292 2010; Abegaz & Midekssa 2021). Although 71% of the Earth's surface is covered by water, only a small fraction is fresh and suitable for drinking, as most water is saline (Edition 2011; Dinka 2018). Freshwater resources are becoming increasingly scarce due to various factors, including population growth, urbanization, and climate change, which exacerbate water stress across many regions of the world (Kumar 2019). It is estimated that more than 300,000 children under the age of five die annually due to a lack of safe drinking water (Lamb et al. 2021), highlighting the urgency of addressing water quality and availability globally. By 2050, it is expected that more than 50% of the world's population will be experiencing moderate water stress, with 80% of those affected living in developing countries (Simelane et al. 2020).

Urbanization is another significant challenge that exacerbates water quality issues. It is anticipated that over two-thirds of the global population will reside in urban areas in the near future, leading to heightened pollution from wastewater, industrial effluents, and other anthropogenic activities (Kim & Kim 2022). Urban land cover changes often result in increased runoff and diminished water quality, necessitating more advanced wastewater treatment processes to manage the growing pollution loads (Uitto & Biswas 2000). In developing countries, the situation is even more critical as access to adequate wastewater treatment and sanitation is limited, with around 40% of the global population lacking access to improved sanitary facilities (Liyanage & Yamada 2017).

The hydrological cycle is intricately linked to water quality, with changes in land use, climate, and human activities influencing both water quantity and quality. Increased runoff and pollution from urban areas degrade water quality, as seen in regions where urban wastewater discharges lead to high levels of biochemical oxygen demand and total coliforms (TC), along with low dissolved oxygen (DO) levels (Karn & Harada 2001). Such environmental pressures are also evident in Sub-Saharan Africa, where groundwater plays a critical role in water supply, especially in arid and semi-arid regions where surface water is scarce or unreliable (Lapworth et al. 2017). However, the quality of groundwater is under increasing threat due to industrial activities, agricultural runoff, and poor waste management practices (Mukhtar et al. 2021).

In Zambia's Copperbelt Province, industrial and mining activities are key drivers of groundwater contamination. The province's extensive mining operations, coupled with rapid urbanization and inadequate wastewater management, have resulted in the contamination of groundwater with heavy metals and other industrial pollutants (Masindi & Abiye 2018; Masindi & Foteinis 2021). Poor agricultural practices, such as the excessive use of fertilizers and pesticides, further degrade water quality (Khatri & Tyagi 2015). Groundwater contamination in this region poses significant public health risks, including hypertension, kidney disease, and other serious health conditions, which burden the healthcare system and reduce the quality of life for affected populations (Ali et al. 2024).

Assessing the quality of groundwater is therefore crucial to ensuring its safety for drinking and other uses. Various methods have been developed to evaluate groundwater quality, including the water quality index (WQI), the fuzzy comprehensive method, and the health risk weight method (Yi et al. 2019; Wu et al. 2020; Ali et al. 2024). Among these, the WQI is particularly favored due to its simplicity, practicality, and versatility in integrating multiple water quality parameters into a single, easily interpretable value (Kumar et al. 2024). The WQI was first introduced by Horton (1965) and has since been widely applied in different regions to assess the suitability of water for drinking and other purposes. In regions like the Copperbelt, where water resources are under significant pressure from industrial and urban activities, the WQI serves as an essential tool for decision-makers to evaluate and communicate water quality effectively.

Despite the widespread use of the WQI in assessing water quality, limited research has focused on its application in regions heavily impacted by mining activities, such as the Copperbelt Province in Zambia. Previous studies in Zambia have primarily addressed industrial contamination and urban runoff but have not specifically examined the impact of mining on groundwater quality in areas like Mufuchani (Nambeye 2017; Banda 2020). This study aims to fill this gap by assessing the suitability of groundwater for drinking in the Mufuchani area using the WQI. By identifying the key pollutants and evaluating the overall water quality, this research will provide valuable insights for local authorities and water managers to develop strategies to protect groundwater resources and ensure safe drinking water for the community.

For this study, Mufuchani, a densely populated slum in Kitwe within Zambia's Copperbelt Province, was selected to analyze groundwater quality and assess the combined impact of mining activities and inadequate sanitation. The Copperbelt region is rich in copper deposits, which significantly influence the spatial patterns of development and settlement. The increase in population in the Copperbelt, particularly in Kitwe City, can be attributed to mining activity, a major pull factor for migration.

The climate of the Copperbelt province is characterized by a humid rainy season, with high rainfall amounts, alongside cooler dry and hot seasons. Temperatures in the Copperbelt typically range from 15 °C in May and June to 32 °C in October, which can further affect groundwater recharge and quality (Hampwaye 2008). Kitwe, the broader city encompassing Mufuchani, spans approximately 31,328 km², accounting for 4.2% of Zambia's total land area (Kitwe 2016). By selecting Mufuchani as the study site, this research aims to provide insights into the groundwater contamination risks in densely populated and industrially influenced regions, highlighting the urgent need for improved water management and pollution control measures.

A mixed-methods research design was employed for this study to ensure a comprehensive understanding of the factors influencing water quality. A cross-sectional survey was conducted, utilizing the World Health Organization (WHO) sanitary survey framework in conjunction with household surveys. This approach enabled the collection of data on household demographic characteristics and the status of water, sanitation, and hygiene practices within the study area. Additionally, an ecological survey was performed to facilitate water sampling from a mix of boreholes and wells. The sampling and subsequent analysis focused on both physico-chemical and biological water quality parameters. Operating procedures adhered to the standards outlined by the American Public Health Association (DeJarnett et al. 2018) for the examination of water and wastewater, ensuring the reliability and validity of the data collected.

Groundwater samples were systematically collected from a total of 20 sampling points, comprising six boreholes and 14 wells. To effectively capture both temporal and spatial variations in groundwater quality, samples were taken bi-monthly. The geographical coordinates of the sample collection sites were recorded using a handheld global positioning system (GPS) and are detailed in Table 1. Water samples were obtained by pumping stagnant water from the boreholes and open wells for a duration of 10 min to ensure the removal of any standing water. Each sample was collected in pre-washed, sterilized 750 mL bottles, which were capped immediately after collection. The bottles were then labeled and carefully transported in a cooler box, maintained at 4 °C, to the Copperbelt University Laboratory for subsequent analysis. Furthermore, physico-chemical parameters including pH, temperature, conductivity, and total dissolved solids (TDS) were measured on-site using multi-probe meters to ensure timely and accurate results. Microbiological water quality analysis was conducted within 24 h of sample collection to maintain the integrity of the samples.

TC and fecal coliforms (FC) concentrations were determined using the Most Probable Number method (DeJarnett et al. 2018) that utilizes the Chromocult broth media. To determine TC 5.2 g of M. Endo Agar Les media were measured and dissolved in 200 mL distilled water, then gently heated to dissolve the media completely. The media was cooled to 40–50 °C in a water bath, then mixed gently and 10 mL was poured into petri dishes to solidify after which the test was carried out using the membrane filtration technique. After 24 h, the petri dishes were removed from the incubator and examined for bacteria colony growth. A 10–15× magnifier microscope was used to count the colonies. The colonies that indicated a yellow color were enumerated as positive colonies for total coliform and were reported as colony forming units (CFU) per 100 mL (DeJarnett et al. 2018). The same procedure was used to determine FC in water samples except that this time m-FC agar media was used.

Water samples were collected using trace metal clean procedures (Clesceri et al. 1998). All equipment used for sample collection, storage and analysis of heavy metals were pre-cleaned using high-purity nitric acid (GFS Chemicals Inc.) and rinsed with copious amounts of Milli-Q water to ensure that they are trace-metal free. After rinsing, the bottles were stored in double-bagged zip-lock polyethylene bags. Such cleaning and storage procedures ensured that there were no detectable metal contaminants in the sampling equipment. The samples were collected in polypropylene bottles and filtered immediately through 0.45 μm and acidified with ultra-pure HNO₃ to pH < 2 and stored at 4 °C prior to heavy metal analyses.

Other physico-chemical parameters that are known to influence the behavior of dissolved metals, such as pH and electrical conductivity (EC), were measured in the field following the procedures outlined in DeJarnett et al. (2018). Heavy metals in the filtrate (0.45 μm) are here operationally defined as ‘dissolved’. The study focused on the dissolved fraction as this fraction is more likely to have measurable biological effects on aquatic organisms (Di Toro et al. 2000). In addition, the dissolved metals have been shown to be similar to the exposure conditions used in toxicity tests (US EPA 2002), allowing for comparisons between standard toxicity tests and field community surveys (Ogendi et al. 2004, 2008). Metal concentrations were determined by the atomic absorption spectrophotometer. In brief, 15 mL of sample was transferred into a vial into which an internal standard containing 40 μg/L ⁶Li, ⁷⁵Ge, ¹¹⁵In, and ²⁰⁹Bi was added. Forty μg/L of ¹⁹⁶Au was added to the sample solutions to stabilize Hg. A standard calibration curve for all the analytes was established on standards prepared in a linear range from 1 to 100 ppb. National Institute of Standards and Testing Reference Material (NIST 1640) and procedural blanks were analyzed for all selected heavy metals.

The data were tested for normality and homogeneity of variance using the Kolmogorov–Smirnov normality test (p ≤ 0.05) and Levene's test for equal variances (p ≤ 0.05), respectively (MINITAB^® Statistical Software for Windows ver. 14). Data satisfying the assumptions of normality was used to compare the heavy metal concentrations in water and fish samples from the selected study sites using analysis of variance to test for differences amongst sites and sampling occasions (α = 0.05).

All the ideal values (V_i) are taken as zero for drinking water except pH and DO (Inayathulla & Paul 2013). In the case of pH, the ideal value is 7.0 (for natural/pure water) while the permissible value is 8.5 (for polluted water). Similarly, for DO, the ideal value is 14.6 mg/L while the standard permissible value for drinking water is 5 mg/L.

Water quality is a key factor in sustainable development, especially in regions like Mufuchani, where groundwater serves as the primary source of drinking water. The results of this study highlight significant challenges posed by both natural processes and human activities that influence water quality. The WQI used in this study provides an integrated assessment of water quality, aligning with the Sustainable Development Goals (SDGs), particularly SDG 6 (Clean Water and Sanitation) and SDG 3 (Good Health and Well-being).

According to the WHO (2011) and ZABS (2010) guidelines for drinking water quality, the permissible limits for EC are 3,000 and 1,500 μS/cm, respectively. In this study, 100% of the water samples recorded EC values below the recommended limit, indicating low salinity levels. However, this does not guarantee that the water is safe for consumption. Low EC values suggest minimal mineral dissolution from the surrounding geology, yet these measurements do not account for contaminants from human and industrial activities (Atta et al. 2022). Conductivity alone cannot reflect the full extent of water quality issues, particularly in regions impacted by industrial activities such as Mufuchani. Similarly, the WHO and ZABS guidelines set the permissible turbidity levels at 5 NTU. Yet, 65% of the water samples in this study surpassed this threshold. Turbidity for well water in this study ranged from 1.94 to 223 NTU whereas the turbidity for borehole water samples ranged from 1.16 to 70.3 NTU with the highest being 70.3 NTU exceeding both the WHO and ZABS guidelines of 5 NTU. The possible contributing factor to high levels of turbidity in water samples could be the nature of the underlying aquifer (Nyirenda 2016). Turbidity, which exceeded permissible limits in most cases, indicates the presence of suspended particles and is often a marker for microbial contamination (WHO 2011; Verma et al. 2020).

The presence of biological contaminants, particularly TC and FC, poses a severe risk to public health. These results are concerning because they indicate fecal contamination, likely from nearby latrines, septic tanks, and inadequate waste disposal systems. All water samples collected from the study area were microbiologically contaminated, with total and fecal coliform levels exceeding the WHO and ZABS guideline limits of 0 CFU/100 mL for fecal coliforms and 0 TC/100 mL for total coliforms. The highest recorded counts were 410 CFU/100 mL and 185 TC/100 mL, respectively. Additionally, 95% of the water samples exhibited elevated levels of both total and fecal coliforms. This situation mirrors findings from studies in other urban areas, such as Amano et al. (2021), where poor sanitation infrastructure led to similar patterns of contamination. The presence of FCs suggests that groundwater sources are highly vulnerable to contamination from human waste, a factor that could lead to outbreaks of waterborne diseases such as cholera and typhoid (Hampwaye 2008). Improving sanitation practices and protecting water sources from contamination must be prioritized to reduce these health risks.

Additionally, the chemical analysis revealed concerning patterns in pH levels, with 65% of the samples showing pH values below WHO and ZABS guidelines of 6.5–8.0. The pH values were as low as 4.84. This suggests that the groundwater is mild to moderately acidic, which can result in corrosive water, increasing the potential for the leaching of metals from pipes (WHO 2011; DeJarnett et al. 2018). The acidic nature of groundwater in this region could be attributed to nearby industrial activities, particularly mining operations, which release sulfuric compounds into the environment, a phenomenon previously observed in similar industrial regions (Khatri & Tyagi 2015; Atta et al. 2022). The elevated pH in certain sampling points, such as SP20, also suggests potential industrial discharges, emphasizing the need for stricter controls on industrial waste disposal to protect groundwater quality. The maximum pH value recorded was 7.84, which falls within the acceptable limits of both WHO and ZABS standards.

Furthermore, heavy metal contamination is another critical issue. Elevated concentrations of copper (Cu) were found in several sampling points, particularly in areas close to industrial sites, where copper concentrations exceeded WHO guidelines (WHO 2011). In this study, the highest concentration of copper was 4.12 mg/L exceeding the WHO and ZABS limits, which are 2 and 1 mg/L, respectively. Copper is often introduced into water through mining and smelting operations, which are prevalent in the Copperbelt Province (Verma et al. 2020). Chronic exposure to elevated copper levels can lead to gastrointestinal and neurological disorders, affecting the liver and kidneys, making this a significant health concern for the local population (Annapoorna & Janardhana. 2015; Nalishuwa 2015; Jing et al. 2016). Similarly, high levels of nickel (Ni) were detected in some samples exceeding the WHO guideline value of 0.02 mg/L. The highest concentration was 3.78 mg/L. There is no guideline value for nickel as per the ZABS standard. Nickel is a known carcinogen, and its presence in groundwater poses long-term health risks. This contamination is likely due to the industrial processes in the area, which require immediate regulatory intervention to prevent further groundwater degradation. In terms of iron, 65% of water samples exceeded the allowable limits of both the WHO and ZABS standards. The highest concentration of iron was 0.47 mg/L from the well exceeding both the WHO and ZABS guideline value of 0.3 mg/L.

The WQI results provide a comprehensive overview of the overall groundwater quality in the region (Ghoderao et al. 2022). Based on the ZABS classification, 5% of water in the study area was excellent water; 15% was very poor water, 25% was good water quality, and 55% was unfit water for drinking water. Similarly, WHO standard classification indicated that 5% of groundwater was categorized as excellent water quality, 10% was classified as good water quality, 15% as very poor water, and 70% as unsuitable and unfit water quality for human consumption (Table 3). This finding aligns with studies such as Amano et al. (2021), which observed that groundwater contamination is common in urban and peri-urban areas affected by industrial activities and inadequate waste management. The high WQI values at several sampling points, particularly SP7 and SP10, suggest severe contamination that encompasses not only biological and chemical parameters but also reflects the cumulative effects of both anthropogenic and natural factors.

When compared with similar studies in other regions, the groundwater quality in Mufuchani is notably worse. For instance, Atta et al. (2022) reported that 35.8% of groundwater samples in their study region were rated as excellent, whereas only 5% of Mufuchani's groundwater achieved this rating. This disparity can be attributed to the intensity of industrial activities in the Copperbelt region and the lack of adequate infrastructure to protect water sources from contamination. These findings indicate a pressing need for policy-driven interventions to monitor and improve water quality, particularly in areas like Mufuchani, where industrial activity is likely to continue to impact the quality of water resources.

This study emphasizes the urgent need for targeted interventions to improve water quality in Mufuchani. Strengthening sanitation infrastructure, implementing filtration and disinfection technologies, and increasing the monitoring of industrial activities are essential steps to safeguard water resources. Policy-makers and other stakeholders must prioritize groundwater protection to ensure safe drinking water for the community and meet the goals outlined by the SDGs including SDG 4 (Quality Education) and SDG 5 (Gender Equality).

The groundwater quality in the study area is significantly compromised, making it unsafe for human consumption without treatment. All sampled stations showed contamination by coliform bacteria, with FC and total coliform levels exceeding WHO and ZABS guidelines. This contamination is largely due to improperly constructed pit-latrines, septic tanks, and sewage systems, as well as the proximity of water sources to refuse dumps, animal waste, and human activity. Additionally, mining activities in the area may contribute to further contamination of the groundwater, with potential risks of heavy metal pollution and other toxic substances leaching into the water. These conditions create pathways for harmful pathogens, posing serious public health risks, including waterborne diseases such as cholera and diarrhea. To address this, we recommend water treatment at both household and community levels, using filtration and disinfection methods. Additionally, public health campaigns are needed to promote better sanitation technologies and improve behaviors related to fecal sludge management, which are essential to reducing contamination and safeguarding community health.

The authors of this manuscript want to express their deep and heartfelt appreciation to the staff and research team at the Copperbelt University for their support all through the study. We are grateful to Mr Sakala William of Copperbelt University's Department of Mathematics, School of Mathematics and Natural Sciences for facilitating sample collection and analysis. Our gratitude also goes to the Pan African Union for the financial support of this study through PAUWES, Algeria. Last but not least, we are grateful to the various reviewers of this manuscript for their valuable comments and feedback.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.