Water quality challenges in rural Ethiopia: insights from the North Mecha district on physiochemical and microbial contamination

Drinking water quality has long been a serious public health problem, particularly in underdeveloped nations where the utilization of sanitary facilities and better water supplies is very limited (Abegaz & Midekssa 2021). In many developing countries, water quality and the potential risk of water-transmitted diseases are major public health problems (Lewoyehu 2021). When access to safe drinking water is intermittent and sources are distant, storing water at home becomes necessary, but this practice can lead to contamination, jeopardizing the fundamental human right to safe drinking water (Bain et al. 2021).

Almost one billion people in the world lack access to safe drinking water, and over five million people die every year from diseases associated with water (Singh & Sharma 2020). Inadequate water and sanitation lead to more than 94% of the four billion instances of diarrhea reported annually worldwide (Birhan et al. 2023).

Most infectious diseases in Ethiopia are associated with unsafe and insufficient water supplies because there has been inadequate access to sanitation and improved water supplies (Berhanu 2015; Duressa et al. 2019; Abegaz & Midekssa 2021). The Escherichia coli (E. coli) count observed in drinking water in various regions of Ethiopia suggested that drinking water safety was compromised (Atumo Ante et al. 2023). As a result, over 75% of health issues in Ethiopia stemmed from infectious diseases linked to unreliable and inadequate water provision, among other factors (Yasin et al. 2015). Similarly, most health concerns among children in the country are transmissible diseases caused by contaminated water and poor sanitation (Duressa et al. 2019). According to Birhan et al. (2023), the occurrence of diarrheal disease among children under five in flood-prone communities of Northwest Ethiopia was recorded at 29.0%. These imply that water quality concerns are common in the country's water supply systems (Damtie et al. 2014; Duressa et al. 2019).

In Ethiopia, where a significant portion of the population relies on inadequate and unsafe water sources, the challenges of ensuring water quality are pronounced (Usman et al. 2017). According to Baztan et al. (2022), the impact of climate change and environmental degradation on the quality and quantity of fresh water supplies had significantly greater challenges to improve access to safe water supply systems. The North Mecha district in the North Gojjam Zone exemplifies this issue, as many households depend on community water points that may not meet safety standards. This study addresses the urgent need to evaluate both the physiochemical and microbial quality of drinking water sources and household storage practices in this region. By conducting a comprehensive cross-sectional analysis during the rainy season, this research aims to identify the prevalence of contaminants such as E. coli and assess various physiochemical parameters against the World Health Organization (WHO) guidelines. The findings provide crucial insights into the current state of drinking water quality in North Mecha, highlighting areas for intervention and improvement to safeguard public health. Ultimately, this study may contribute to efforts aimed at enhancing water safety within rural Ethiopian communities.

Water samples were taken from boreholes with hand pumps, protected springs, public taps, and protected dug wells with hand pumps (PDWHP) in each enumeration area (EAs) for the physiochemical and E. coli analysis (Table 1). The study was conducted during the rainy season from July to September 2022 and focused on only community-managed water sources and these water sources are used by more than 26,774 people. Samples were also collected from households' drinking water storages for E. coli analysis. Physiochemical parameters that were tested include turbidity, temperature, electrical conductivity (EC), pH, free residual chlorine, sulfate, phosphate, iron, ammonia, total hardness, calcium hardness, and nitrate. Furthermore, E. coli was specifically measured as an indicator organism for evaluating microbial water quality.

A sanitary survey was performed at the water sources, utilizing a structured questionnaire that required ‘yes’ or ‘no’ responses to identify key factors contributing to water contamination. The survey questions were adapted from the WHO guidelines for sanitary surveys. The assessment classifies sanitary risk levels into four categories: low (scores between 0 and 2), medium (3–5), high (6–8), and very high (over 8).

A total of 24 EAs were selected from the district using probability proportional to size sampling (PPS) methods used by Fentie et al. (2024), which is a sampling procedure under which the probability of a unit being selected is proportional to the size of the ultimate unit (Latpate et al. 2021). In the PPS method, larger clusters are assigned a higher probability of selection during the first stage of sampling, while smaller clusters have a lower probability. To ensure balance in the sampling process, individuals within the larger clusters are given a reduced chance of being selected. This compensatory mechanism helps to maintain an equitable sampling distribution across all clusters. The number of households per EA was obtained from the Central Statistical Agency. Simple random sampling techniques were used to select households for sampling from each EA. Additionally, samples were collected from improved water sources found in the selected EAs. A joint monitoring program defines improved drinking water sources as those that have the potential to deliver safe water due to their design and construction, which protect from outside contamination (Bain et al. 2015).

For the purpose of the E. coli test samples greater than 100 mL of water were collected directly into a Whirl-Pak bag containing sodium thiosulfate, which is used to neutralize residual chlorine in the sampled water, after which the sample was promptly placed in a cooling box for transportation. Water samples from the sources were collected directly at the sites. Household samples were collected to assess the risk of recontamination after water is stored in the households' storage; hence, respondents were asked to provide a glass of drinking water in the same manner they would typically serve it to a guest or a child. This approach assumes that if there is variation in the drinking water quality used within a household, children, and guests are typically offered the highest quality water available (Keleb et al. 2022).

The physicochemical parameters, such as EC, temperature, and pH, were measured using the Hanna Instruments HI98129 Meter (Hanna Instruments Ltd, Leighton Buzzard, UK) (Fentie et al. 2024). Free residual chlorine and turbidity measurements were conducted using a LaMotte Octaslide Chlorine Tester and a LaMotte™ Turbidity meter (LaMotte™, Chestertown, MD, USA), respectively. All these parameters were tested directly at the sampling sites. The pH measurements were performed after calibrating the pH electrode using the manufacturer's buffer solutions. For EC measurements, the EC electrode was calibrated with a standard KCl solution prior to sampling from the sources. Additionally, the turbidity meter was calibrated with standard solutions provided by the manufacturer. A 10 mL water sample was added to test tubes, and its turbidity was measured in Nephelometric Turbidity Units (NTU) (Lewoyehu 2021).

The phosphate, iron, ammonia, nitrate, sulfate, and hardness levels in water sources were tested using a Palintest photometer 7500 (Palintest Ltd, Gateshead, UK) in the central laboratory of Bahir Dar Institute of Technology. The membrane filtration technique followed by Lewoyehu was employed to test the presence of E. coli in samples (Lewoyehu 2021). A 100 mL sample was vacuum-filtered through sterile 45-μm Millipore S-pack type HA membrane filters (HACH, Manchester, UK). The membrane filter, which captured the particles, was then placed in a Petri dish containing a membrane pad soaked in culture media (membrane lauryl sulfate broth) that selectively supports the growth of E. coli. These prepared Petri dishes were incubated at 44 °C for 24 h. After incubation, the yellow colonies indicative of E. coli were counted and documented. However, filtering excessively turbid water samples posed challenges during the process; in such cases, a smaller volume of the sample was filtered, and results were adjusted accordingly using a dilution factor.

Blank and duplicate samples with known water parameter values were analyzed to verify the accuracy of the water sample analysis procedure. This process ensured that variability in results was not due to errors in sample collection or laboratory analysis. A field blank sample from a sealed water bottle was tested for E. coli once a week every Wednesday to verify that the collection process was free from contamination. To ensure the accuracy of the field test procedure and equipment, a duplicate sample was collected from the water point every Friday. To ensure the quality of the membrane lauryl sulfate broth and the laboratory analysis methods, daily checks of a laboratory blank sample during the E. coli test were conducted. Field test instruments were calibrated weekly and verified daily, and if verification was unsuccessful, standard solutions were used for recalibration. Also, training was provided to laboratory technicians and data collectors to uphold data quality standards.

The measured E. coli count and physicochemical characteristics of the water were compared to both national and international drinking water standards to assess if the water quality met the required levels (Yasin et al. 2015). To calculate the related health risks of drinking water, the amount of E. coli in a 100 mL sample was measured. E. coli counts up to 100 CFU/100 mL were conducted on all samples. The E. coli test result of the sample was recorded as 101, which stands for ‘too numerous to count’, if the E. coli count was more than 100 CFU/100 mL. To improve overall comprehension and understanding of the degree of fecal contamination in rural water supply systems and household storage, color coding was used. In this color-coding system, a blue color code represented the absence of E. coli detection (<1 CFU/100 mL), indicating a safe category. The green color code (1–10 CFU/100 mL) indicated a low-risk category, while the yellow color code (11–100 CFU/100 mL) represented an intermediate-risk category and the orange color code (101–1,000 CFU/100 mL) denoted a high-risk category (Duressa et al. 2019; Sitotaw et al. 2021; Fentie et al. 2024).

The statistical analysis was performed using Excel and R programming (R 4.1.2, RStudio 2021.11.01) language. Descriptive statistics, such as mean, minimum, and maximum, were used to show the data characteristics. The Shapiro–Wilk test p-value of all physiochemical parameters was used to test the dataset for normality. The Kruskal–Walli's rank sum test was employed to determine significant variations in each parameter's values among the water sources (Duressa et al. 2019; Sitotaw et al. 2021).

The microbial quality of drinking water was tested by the indicator microorganisms whose presence indicates fecal contamination. Samples were collected from boreholes with hand pumps, PDWHPs, protected springs, and public taps for the E. coli test. Additionally, samples were collected from 96 households that obtained water from the corresponding water sources.

Nearly half of the samples collected from protected springs were free from E. coli contamination. More than 16% of samples from protected springs fell into high health risk categories. This result is lower compared to the finding of Fentie et al. (2024) which studied the Ferta district, Northwest Ethiopia, and found that 46.7% of samples from protected springs fell into high health risk categories.

Access to improved water sources has profound effects on public health, significantly reducing the incidence of waterborne diseases and enhancing overall community well-being (Esrey et al. 1991). However, despite the increased access to improved water sources in the study area and other regions of East Africa (Terefe et al. 2024), the quality of water from a significant proportion of these water sources often remains suboptimal (Kumpel & Nelson 2013; Yasin et al. 2015; Lewoyehu 2021; Fentie et al. 2024). This might be attributed to several factors, including inadequate protection of water sources, inadequate sanitation and hygiene practices, socioeconomic challenges such as community poverty levels, and varying degrees of community literacy (Alemayehu et al. 2020; Aragaw et al. 2023). The detection of fecal contamination in improved water sources implied the necessity for comprehensive protective measures for these water sources, alongside enhanced sanitation practices and sustained improvements in water accessibility.

Water sources with low risk of sanitary levels did not indicate their safety particularly concerning E. coli contamination, a similar pattern of E. coli levels across the sanitary risk score was shown by Fentie et al. (2024). Other studies also confirmed a lack of correlation between sanitary risk score and E. coli prevalence recommends not to expect a perfect correlation and theses two provide distinct information (Alemayehu et al. 2020; Kelly et al. 2021). Based on the study findings, although low sanitary risk levels are indicative of certain protective measures, they do not assure the absence of E. coli contamination, necessitating a multifaceted approach to water quality assessment and management.

Understanding the physicochemical properties of drinking water is fundamental for assessing its suitability for human consumption and identifying potential health risks. The data obtained from these analyses not only provide insights into the overall quality of drinking water but also offer valuable information for policymakers, public health officials, and community stakeholders. A summary of key physicochemical parameters measured to elucidate the findings of the study is presented in Table 2.

The pH of drinking water usually has no direct health impact on consumers, though it is one of the most important water quality parameters (Nas & Berktay 2010; WHO 2017). The mean pH values in the water samples were from 6.05 to 7.67 across different water point types. The pH levels of water from public taps and boreholes with hand pumps consistently fell within the WHO-recommended range of 6.5–8.5, indicating suitability for human consumption. However, around 78.6% of the samples were out of the recommended range of pH. All the samples taken from protected springs and around 83% of samples taken from PDWHPs had a pH value of below 6.5. A similar observation was made in the research conducted by Fentie et al. (2024), on the South Gondar Zone, which reported that the pH level of water samples from protected springs was found to be acidic. Another study in Guinea Bissau also confirmed water in hand-dug wells is acidic compared to boreholes (Machado et al. 2022). The results of the Kruskal–Wallis test showed that there was a significant variation in pH among different water source types (p < 0.01). The higher level of acidity in the protected springs and protected dug well with hand pump might be due to the interaction of water with the adjacent acidic soil (Yasin et al. 2015), and the CO₂ redox reaction in the water might also reduce the pH level (WHO 2007).

The mean turbidity of water sources in the study area ranged from 1.04 to 15.92 NTU. The result showed that around 36% of samples exceeded the national standard (5 NTU). As indicated in Table 2, relatively high turbidity was recorded in protected springs and PDWHPs. Around 38.5% of the samples taken from protected springs and 48% of the samples taken from PDWHPs had turbidity values of more than the WHO-recommended range. The sanitary survey result showed a high sanitary risk score in these water sources. The high mean turbidity value in these might be due to the effluents from domestic products, runoff from agricultural activities, and fecal contamination from farms (Azis et al. 2015), since the study was conducted in the rainy season. Although drinking water turbidity by itself is not associated with potential health threat consumption of highly turbid water might pose a health risk (Ribeiro et al. 2018) as it might shield pathogens from disinfectants like chlorine and provide substrate for pathogen growth in water. Implementing water safety plans and controlling runoff in the area can minimize the introduction of sediments, nutrients and pathogens into water sources. The results of the Kruskal–Wallis test showed that there was a significant variation in turbidity among different water source types (p < 0.01).

According to the survey conducted during this study, chlorine was added to water sources once in 1–3 months. In the present study, 89.3% of the samples taken had no free residual chlorine, and it was detected in only 11% of samples tested. This is because the chlorine was not regularly added to the water supply systems. Of the samples tested, only one sample containing free residual chlorine was positive for E. coli detection, whereas 19 samples without free residual chlorine tested positive for E. coli. This finding highlights the potential effectiveness of free residual chlorine in controlling E. coli contamination. The significantly higher detection rate in samples without free residual chlorine underscores the importance of maintaining adequate chlorine levels to ensure microbial safety in water systems. Chandra et al. (2016) suggest that the presence of free residual chlorine in drinking water is linked with the absence of disease-causing agents, thereby serving as an indicator of drinking water safety.

The nitrate value of sampled water ranged from 0.21 to 4.47 mg/L and almost all the samples' nitrate concentration conformed to the WHO standard (Table 2). The highest nitrate level was recorded in a protected dug well with a hand pump. The finding in this study is consistent with a study conducted in Northwest Ethiopia that reported the average nitrate levels (3.3 mg N-NO₃/L in wells and 1.4 mg N-NO₃/L in springs) were within standard limits, but dug wells in agricultural fields had higher nitrate concentrations than those in grazing areas (Akale et al. 2017). The result was much lower than that of Chen et al. (2017) who conducted research in Northwest China and found that 60% of the samples had exceeded the WHO's recommended nitrate level in drinking water. The ammonia–nitrogen concentrations of water samples ranged from 0.01 to 0.92 mg/L. Almost all the samples showed safe levels of ammonia as compared with the WHO standards.

The iron concentration in the sample ranged from 0 to 0.92 mg/L, and the results showed that 20% of the examined sample's iron concentrations were out of the range of the WHO standard for drinking water (0.3 mg/L). From the survey, users have complained that the water had taste and/or odor problems, especially in protected boreholes with hand pump water sources. The results of the Kruskal–Wallis test show that there was no significant variation in iron among different water source types (p = 0.146).

The mean EC of water sources in the study area ranged from 134.6 to 285.7 μS/cm, which indicates that all the samples were within the allowable limit of the WHO standard. The maximum mean EC was recorded in the public taps. This result agrees with Sitotaw et al. (2021), which shows that the maximum EC was recorded in tap water. The EC of water can be identified as an indicator of salinity content in water (Ratnayake et al. 2013; Ratnayake et al. 2017). The temperature of analyzed samples ranged from 20.23 to 23.2 °C and almost all the samples of water temperature delivered to the communities from various sources were within the WHO's authorized level of drinking water guidelines (from 15 to 25 °C).

The phosphate level in the study area ranged from 0.02 to 2.5 mg/L which fell within the WHO-recommended level. As indicated in Table 2, a relatively high value of phosphate was recorded in boreholes with hand pumps. The sulfate content in the study area ranged from 0 to 48 mg/L which indicates all the samples fell below the WHO standard (250 mg/L). A relatively high amount of sulfate was recorded in the protected spring water points. The sulfate presence in drinking water might cause a detectable taste, and very high amounts may create gastrointestinal effects in consumers (WHO 2017).

The calcium hardness of sampled water ranged from 2 to 111 mg/L as CaCO₃, whereas the total hardness of sampled water ranged from 22 to 240 mg/L as CaCO₃. The result also shows that the total hardness and calcium hardness of the water samples were within the permissible limit of WHO standards. Excessive water hardness can raise the risk of nephrolithiasis, osteoporosis, colorectal cancer, stroke and hypertension, coronary artery disease, obesity, and insulin resistance (Akram 2018).

There was also a high correlation between EC and pH of water (0.72). A study conducted by Ratnayake et al. (2017) showed that there was a good positive (R = 0.65) correlation between conductivity and pH of water. Another study conducted by Nwoye et al. (2014) also revealed a strong correlation between pH and conductivity of sea water. There was no strong correlation shown between the other water quality parameters across all water sources in the study area.

This study provides valuable insights into the physicochemical and microbial quality of drinking water from different sources and household storage. All the samples taken from protected springs and around 83% of samples taken from PDWHPs had a pH value of below 6.5. Around 38.5% of the samples taken from protected springs and 48% of the samples taken from PDWHPs had turbidity values of more than the WHO-recommended range. The results of the study showed that 20% of the examined sample's iron concentrations were out of the range of the WHO standard. The sanitary survey results also showed that there was a high sanitary risk score in protected springs and PDWHP water sources. E. coli was detected in 42.9% of the samples collected at the POC and 47.9% of the samples collected from the households' storage. The results of this study showed that there was an increase in E. coli contamination of drinking water at the household level; hence, public health is under threat. The study highlights that improved water sources do not necessarily ensure safety, as ongoing contamination issues are influenced by factors such as insufficient protection of these sources, inadequate sanitation practices, and socioeconomic challenges. These findings suggested that water sources protection and treatment, and water treatment at the household level should be implemented to improve the quality of drinking water supplied to the rural community. This study did not include the seasonal variation in water quality. Future studies should focus on identifying contributing factors to water quality degradation. Additionally, future studies should investigate the specific factors contributing to the reduction of pH in water sources such as protected springs and dug wells in the study area.

Y.A., M.F., and E.A. conceptualized the study, investigated the work, developed the methodology, and rendered support in data curation. Y.A. provided the software, rendered support in formal analysis, and wrote the original draft preparation, Y.A., E.A., M.F., T.T, and D.A. validated the process, reviewed and edited the article, and visualized the work. D.A. supervised the work. E. A. rendered support in project administration. D.A. and E. A. rendered support in funding acquisition. All authors read and approved the final manuscript.

This research was funded by the Conrad N. Hilton Foundation grant number 27064.

The researchers would like to thank the Aquaya Institute for their support in establishing data collection and water sample testing protocol and funding the publication. We are also grateful to Anna Murray and Meseret Dessalegn for their support during data collection and cleaning in the study.

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

The authors declare there is no conflict.