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Assessment of Drinking Water Quality Using Water Quality Index: A Review

• Review Paper
• Published: 30 January 2023
• Volume 8 , article number  6 , ( 2023 )

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• Atanu Manna 1 &
• Debasish Biswas   ORCID: orcid.org/0000-0001-8747-0934 2  

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Nowadays, declining water quality is a significant concern for the world because of rapid population growth, agricultural and industrial activity enhancement, global warming, and climate change influencing hydrological cycles. Assessing water quality becomes necessary by using a suitable method to reduce the risk of geochemical contaminants. Water’s physical and chemical properties are compared to a standard guideline to determine its quality. The water quality index (WQI) model is a commonly helpful technique for evaluating surface and groundwater quality. The model mainly employs aggregation techniques to diminish large amounts of data to a sole value. The WQI model has been used across the globe to assess ground and surface water using regional standards. The model has become popular for its ease of use and general structure. Typically, WQI models include five stages: (1) choosing water quality indicators, (2) generating sub-parameters for each variable, (3) calculating variable weighting numbers, (4) aggregating sub-parameters to finding the total WQI value, and (5) classification of WQI value to highlight the category of water quality. In addition, the model creates ambiguity when converting vast volumes of data into a single value. The study considered 2011–2021 blinded peer-reviewed articles and book chapters to assess WQI models and their application in evaluating drinking water quality. This study mainly concentrated on the comparison of WQI models and their applications. The study also focused on the selection of parameters and problems associated with the accuracy of the models.

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Damo R, Icka P (2013) Evaluation of water quality index for drinking water. Pol J Environ Stud 22(4):1045–1051.  https://www.researchgate.net/profile/Pirro-Icka/publication/287957321_Evaluation_of_Water_Quality_Index_for_Drinking_Water/links/5923fd63aca27295a8aad7c1/Evaluation-of-Water-Quality-Index-for-Drinking-Water.pdf . Accessed 6 Nov 2021

Uddin MG, Nash S, Olbert AI (2021) A review of water quality index models and their use for assessing surface water quality. Ecol Indic 122:107218. https://doi.org/10.1016/j.ecolind.2020.107218

Article   CAS   Google Scholar  

Uddin MG, Moniruzzaman M, Quader MA, Hasan MA (2018) Spatial variability in the distribution of trace metals in groundwater around the Rooppur nuclear power plant in Ishwardi, Bangladesh. Groundw Sustain Dev 7:220–231. https://doi.org/10.1016/j.gsd.2018.06.002

Article   Google Scholar  

Egbueri JC, Ameh PD, Unigwe CO (2020) Integrating entropy-weighted water quality index and multiple pollution indices towards a better understanding of drinking water quality in Ojoto area, SE Nigeria. Sci African 10:e00644. https://doi.org/10.1016/j.sciaf.2020.e00644

Ortega DJP, Pérez DA, Américo JHP, de Carvalho SL, Segovia JA (2016) Development of index of resilience for surface water in watersheds. J Urban Environ Eng 10(1):72–82. https://doi.org/10.4090/juee.2016.v10n1.007282

Alcamo J (2019) Water quality and its interlinkages with the sustainable development goals. Curr Opin Environ Sustain 36:126–140. https://doi.org/10.1016/j.cosust.2018.11.005

Li P, Wu J (2019) Drinking water quality and public health. Exposure and Health 11(2):73–79. https://doi.org/10.1007/s12403-019-00299-8

Guo X, Zhang XX, Yue HC (2018) Evaluation of hierarchically weighted principal component analysis for water quality management at Jiaozuo mine. Int Biodeterior Biodegradation 128:182–185. https://doi.org/10.1016/j.ibiod.2017.11.012

Ighalo JO, Adeniyi AG (2020) A comprehensive review of water quality monitoring and assessment in Nigeria. Chemosphere, 127569. https://doi.org/10.30564/jees.v3i1.2900

Motlagh AM, Yang Z, Saba H (2020) Groundwater quality. Water Environ Res 92(10):1649–1658. https://doi.org/10.1002/wer.1412

Zhang Q, Xu P, Qian H (2020) Groundwater quality assessment using improved water quality index (WQI) and human health risk (HHR) evaluation in a semi-arid region of northwest China. Exposure and Health 12(3):487–500. https://doi.org/10.1007/s12403-020-00345-w

Egbueri JC, Ezugwu CK, Ameh PD, Unigwe CO, Ayejoto DA (2020) Appraising drinking water quality in Ikem rural area (Nigeria) based on chemometrics and multiple indexical methods. Environ Monit Assess 192(5). https://doi.org/10.1007/s10661-020-08277-3

Fu B, Merritt WS, Croke BFW, Weber TR, Jakeman AJ (2019) A review of catchment-scale water quality and erosion models and a synthesis of future prospects. Environ Model Softw 114:75–97. https://doi.org/10.1016/j.envsoft.2018.12.008

Hui T, Xiujuan L, Qifa S, Qiang L, Zhuang K, Yan G (2020) Evaluation of drinking water quality using the water quality index (WQI), the synthetic pollution index (SPI) and geospatial tools in Lianhuashan District, China. Pol J Environ Stud 30(1):141–153. https://doi.org/10.15244/pjoes/120765

Lumb A, Sharma TC, Bibeault J-F (2011) A review of genesis and evolution of water quality index (WQI) and some future directions. Water Qual Expo Health 3(1):11–24. https://doi.org/10.1007/s12403-011-0040-0

Solangi GS, Siyal AA, Babar MM, Siyal P (2019a) Application of water quality index, synthetic pollution index, and geospatial tools for the assessment of drinking water quality in the Indus Delta, Pakistan. Environ Monit Assess, 191(12). https://doi.org/10.1007/s10661-019-7861-x

Abba SI, Hadi SJ, Sammen SS, Salih SQ, Abdulkadir RA, Pham QB, Yaseen ZM (2020) Evolutionary computational intelligence algorithm coupled with self-tuning predictive model for water quality index determination. J Hydrol 587:124974. https://doi.org/10.1016/j.jhydrol.2020.124974

Singh B, Sihag P, Singh VP, Sepahvand A, Singh K (2021) Soft computing technique-based prediction of water quality index. Water Supply. https://doi.org/10.2166/ws.2021.157

Tung TM, Yaseen ZM (2021) Deep learning for prediction of water quality index classification: tropical catchment environmental assessment. Nat Resour Res 30:4235–4254. https://doi.org/10.1007/s11053-021-09922-5

Banda TD, Kumarasamy M (2020) Development of a universal water quality index (UWQI) for South African river catchments. Water 12(6):1534. https://doi.org/10.3390/W12061534

Mamun M, An KG (2021) Application of multivariate statistical techniques and water quality index for the assessment of water quality and apportionment of pollution sources in the Yeongsan river, South Korea. Int J Environ Res Public Health 18(16):8268. https://doi.org/10.3390/ijerph18168268

Tripathi M, Singal SK (2019) Use of principal component analysis for parameter selection for development of a novel water quality index: a case study of river Ganga India. Ecol Ind 96:430–436. https://doi.org/10.1016/j.ecolind.2018.09.025

Abbasnia A, Yousefi N, Mahvi AH, Nabizadeh R, Radfard M, Yousefi M, Alimohammadi M (2019) Evaluation of groundwater quality using water quality index and its suitability for assessing water for drinking and irrigation purposes: case study of Sistan and Baluchistan province (Iran). Hum Ecol Risk Assess Int J 25(4):988–1005. https://doi.org/10.1080/10807039.2018.1458596

Jha MK, Shekhar A, Jenifer MA (2020) Assessing groundwater quality for drinking water supply using hybrid fuzzy-GIS-based water quality index. Water Res 179:115867. https://doi.org/10.1016/j.watres.2020.115867

Mukate S, Wagh V, Panaskar D, Jacobs JA, Sawant A (2019) Development of new integrated water quality index (IWQI) model to evaluate the drinking suitability of water. Ecol Ind 101:348–354. https://doi.org/10.1016/j.ecolind.2019.01.034

Al-Hamdany NAS, Al-Shaker YMS, Al-Saffawi AYT (2020) Water quality assessment using the NSFWQI model for drinking and domestic purposes: a case study of groundwater on the left side of Mosul city, Iraq. Plant Archives 20(1):3079–3085. http://www.plantarchives.org/20-1/3079-3085(6183).pdf . Accessed 6 Nov 2021

Bouteraa O, Mebarki A, Bouaicha F, Nouaceur Z, Laignel B (2019) Groundwater quality assessment using multivariate analysis, geostatistical modeling, and water quality index (WQI): a case of study in the Boumerzoug-El Khroub valley of Northeast Algeria. Acta Geochimica 38(6):796–814. https://doi.org/10.1007/s11631-019-00329-x

RadFard M, Seif M, GhazizadehHashemi AH, Zarei A, Saghi MH, Shalyari N, Morovati R, Heidarinejad Z, Samaei MR (2019) Protocol for the estimation of drinking water quality index (DWQI)in water resources: artificial neural network (ANFIS)and Arc-Gis. MethodsX 6:1021–1029. https://doi.org/10.1016/j.mex.2019.04.027

Solangi GS, Siyal AA, Babar MM, Siyal P (2019) Evaluation of drinking water quality using the water quality index (WQI), the synthetic pollution index (SPI) and geospatial tools in Thatta district, Pakistan. Desalination Water Treat 160:202–213. https://doi.org/10.5004/dwt.2019.24241

Solangi GS, Siyal AA, Babar MM, Siyal P (2020) Groundwater quality evaluation using the water quality index (WQI), the synthetic pollution index (SPI), and geospatial tools: a case study of Sujawal district, Pakistan. Human Ecol Risk Assess 26(6):1529–1549. https://doi.org/10.1080/10807039.2019.1588099

Tiwari AK, Singh AK, Mahato MK (2018) Assessment of groundwater quality of Pratapgarh district in India for suitability of drinking purpose using water quality index (WQI) and GIS technique. Sustain Water Resour Manag 4(3):601–616. https://doi.org/10.1007/s40899-017-0144-1

Tiwari S, Babbar R, Kaur G (2018). Performance evaluation of two ANFIS models for predicting water quality Index of River Satluj (India). Adv Civil Eng 2018. https://doi.org/10.1155/2018/8971079

Seifi A, Dehghani M, Singh VP (2020) Uncertainty analysis of water quality index (WQI) for groundwater quality evaluation: application of Monte-Carlo method for weight allocation. Ecol Indic 117:106653. https://doi.org/10.1016/j.ecolind.2020.106653

Dutta N, Thakur BK, Nurujjaman M, Debnath K, Bal DP (2022) An assessment of the water quality index (WQI) of drinking water in the Eastern Himalayas of South Sikkim India. Groundw Sustain Dev 17:100735. https://doi.org/10.1016/j.gsd.2022.100735

Verma P, Singh PK, Sinha RR, Tiwari AK (2020) Assessment of groundwater quality status by using water quality index (WQI) and geographic information system (GIS) approaches: a case study of the Bokaro district, India. Appl Water Sci 10(1):1–16. https://doi.org/10.1007/s13201-019-1088-4

Gorai AK, Hasni SA, Iqbal J (2016) Prediction of ground water quality index to assess suitability for drinking purposes using fuzzy rule-based approach. Appl Water Sci 6(4):393–405. https://doi.org/10.1007/s13201-014-0241-3

Akhtar N, Ishak MIS, Ahmad MI, Umar K, MdYusuff MS, Anees MT, Qadir A, Ali Almanasir YK (2021) Modification of the water quality index (WQI) process for simple calculation using the multi-criteria decision-making (MCDM) method: a review. Water 13(7):905. https://doi.org/10.3390/w13070905

Aljanabi ZZ, Al-Obaidy A-HMJ, Hassan FM (2021) A brief review of water quality indices and their applications. IOP Conf Ser: Earth Environ Sci 779(1):12088. https://doi.org/10.1088/1755-1315/779/1/012088

Soumaila KI, Niandou AS, Naimi M, Mohamed C, Schimmel K, Luster-Teasley S, Sheick NN (2019) A systematic review and meta-analysis of water quality indices. J Agric Sci Technol B B(9):1–14. https://doi.org/10.17265/2161-6264/2019.01.001

Abed BS, Farhan A-R, Ismail AH, Al Aani S (2021) Water quality index toward a reliable assessment for water supply uses: a novel approach. Int J Environ Sci Technol, 1–14. https://doi.org/10.1007/s13762-021-03338-7

Wagh VM, Mukate SV, Panaskar DB, Muley AA, Sahu UL (2019) Study of groundwater hydrochemistry and drinking suitability through Water Quality Index (WQI) modelling in Kadava river basin, India. SN Applied Sciences 1(10):1–16. https://doi.org/10.1007/s42452-019-1268-8

Gupta S, Gupta SK (2021) A critical review on water quality index tool: genesis, evolution and future directions. Eco Inform 63:101–299. https://doi.org/10.1016/j.ecoinf.2021.101299

Hui T, Jizhong D, Qifa S, Yan G, Zhuang K, Hongtao J (2021) Evaluation of shallow groundwater for drinking purpose based on water quality index and synthetic pollution index in Changchun New District, China. Environ Forensic 22(1–2):189–204. https://doi.org/10.1080/15275922.2020.1834024

Ewaid SH, Abed SA, Al-Ansari N, Salih RM (2020) Development and evaluation of a water quality index for the Iraqi rivers. Hydrology 7(3):67. https://doi.org/10.3390/HYDROLOGY7030067

Ukah BU, Ameh PD, Egbueri JC, Unigwe CO, Ubido OE (2020) Impact of effluent-derived heavy metals on the groundwater quality in Ajao industrial area, Nigeria: an assessment using entropy water quality index (EWQI). Int J Energy Water Resour, 1–14. https://doi.org/10.1007/s42108-020-00058-5

Tiri A, Belkhiri L, Mouni L (2018) Evaluation of surface water quality for drinking purposes using fuzzy inference system. Groundw Sustain Dev 6:235–244. https://doi.org/10.1016/j.gsd.2018.01.006

Alver A (2019) Evaluation of conventional drinking water treatment plant efficiency according to water quality index and health risk assessment. Environ Sci Pollut Res 26(26):27225–27238. https://doi.org/10.1007/s11356-019-05801-y

Saw S, Mahato JK, Singh PK (2021). Suitability Evaluation of CCME-WQI and GWQI for the modeling of groundwater and human health risk assessment of heavy metals - Eastern India. Res Square, 0–24. https://doi.org/10.21203/rs.3.rs-1000020/v1

Patil VBB, Pinto SM, Govindaraju T, Hebbalu VS, Bhat V, Kannanur LN (2020) Multivariate statistics and water quality index (WQI) approach for geochemical assessment of groundwater quality—a case study of Kanavi Halla Sub-Basin, Belagavi, India. Environ Geochem Health 42(9):2667–2684. https://doi.org/10.1007/s10653-019-00500-6

Nath BK, Chaliha C, Bhuyan B, Kalita E, Baruah DC, Bhagabati AK (2018) GIS mapping-based impact assessment of groundwater contamination by arsenic and other heavy metal contaminants in the Brahmaputra River valley: a water quality assessment study. J Clean Prod 201:1001–1011. https://doi.org/10.1007/s10462-021-10007-1

Sutadian AD, Muttil N, Yilmaz AG, Perera BJC (2016) Development of river water quality indices—a review. Environ Monit Assess 188(1):58. https://doi.org/10.1007/s10661-015-5050-0

Swamee PK, Tyagi A (2007) Improved method for aggregation of water quality subindices. J Environ Eng 133(2):220–225. https://doi.org/10.1061/(ASCE)0733-9372(2007)133:2(220)

Uddin G, Nash S, Olbert AI (2022) Optimisation of parameters in a water quality index model using principal component analysis. Proc 39th IAHR World Congr 19:5739–5744. https://doi.org/10.3850/IAHR-39WC2521711920221326

Uddin MG, Nash S, Rahman A, Olbert AI (2022) A comprehensive method for improvement of water quality index (WQI) models for coastal water quality assessment. Water Research 219:118532. https://doi.org/10.1016/j.watres.2022.118532

Uddin MG, Nash S, Rahman A, Olbert AI (2023) Assessing optimisation techniques for improving water quality model. J Clean Prod 385:135671. https://doi.org/10.1016/j.jclepro.2022.135671

Uddin MG, Nash S, Rahman A, Olbert AI (2023) Performance analysis of the water quality index model for predicting water state using machine learning techniques. Process Saf Environ Prot 169:808–828. https://doi.org/10.1016/j.psep.2022.11.073

Uddin MG, Nash S, Rahman A, Olbert AI (2023) A novel approach for estimating and predicting uncertainty in water quality index model using machine learning approaches. Water Res 229:119422. https://doi.org/10.1016/j.watres.2022.119422

Islam M, Mostafa MG (2021) Development of an integrated irrigation water quality index (IIWQIndex) model. Water Supply 22(2):2322–2337. https://doi.org/10.2166/ws.2021.378

Wagh VM, Panaskar DB, Muley AA, Mukate SV (2017) Groundwater suitability evaluation by CCME WQI model for Kadava River Basin, Nashik, Maharashtra, India. Model Earth Syst Environ 3(2):557–565. https://doi.org/10.1007/s40808-017-0316-x

Elbeltagi A, Pande CB, Kouadri S, Islam ARM (2022) Applications of various data-driven models for the prediction of groundwater quality index in the Akot basin, Maharashtra India. Environ Sci Pollut Res 29(12):17591–17605. https://doi.org/10.1007/s11356-021-17064-7

Hossain M, Patra PK (2020) Water pollution index–a new integrated approach to rank water quality. Ecol Indic 117:106668. https://doi.org/10.1016/j.ecolind.2020.106668

Barbosa Filho J, de Oliveira IB (2021) Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses. Sci Rep 11(1):1–22. https://doi.org/10.1038/s41598-021-95912-9

Gradilla-Hernández MS, de Anda J, Garcia-Gonzalez A, Montes CY, Barrios-Piña H, Ruiz-Palomino P, Díaz-Vázquez D (2020) Assessment of the water quality of a subtropical lake using the NSF-WQI and a newly proposed ecosystem specific water quality index. Environ Monit Assess 192(5):1–19. https://doi.org/10.1007/s10661-020-08265-7

Najafzadeh M, Homaei F, Farhadi H (2021) Reliability assessment of water quality index based on guidelines of national sanitation foundation in natural streams: integration of remote sensing and data-driven models. Artif Intell Rev 56(4):4619–4651. https://doi.org/10.1007/s10462-021-10007-1

Zotou I, Tsihrintzis VA, Gikas GD (2019) Performance of seven water quality indices (WQIs) in a Mediterranean River. Environ Monit Assess 191(8):1–14

Banda, Kumarasamy MA (2020) Review of the existing water quality indices (WQIs). J Phys Opt 39(2):1–19. https://www.researchgate.net/profile/Talent-Banda/publication/343430598_A_Review_of_the_Existing_Water_Quality_Indices_WQIs/links/5f299e76299bf13404a22edc/A-Review-of-the-Existing-Water-Quality-Indices-WQIs.pdf . Accessed 11 Nov 2021

Kamboj V, Kamboj N, Bisht A (2020) An overview of water quality indices as promising tools for assessing the quality of water resources. Agro Environ Media - Agric Environ Sci Acad pp. 188–214. https://doi.org/10.26832/aesa-2020-aepm-013

Haider H, Ghumman AR, Al-Salamah IS, Thabit H (2020) Assessment framework for natural groundwater contamination in arid regions: development of indices and wells ranking system using fuzzy VIKOR method. Water 12(2):423. https://doi.org/10.3390/w12020423

Pak HY, Chuah CJ, Tan ML, Yong EL, Snyder SA (2021) A framework for assessing the adequacy of water quality index–quantifying parameter sensitivity and uncertainties in missing values distribution. Sci Total Environ 751(10):141982. https://doi.org/10.1016/j.scitotenv.2020.141982

Smith DG (1990) A better water quality indexing system for rivers and streams. Water Res 24(10):1237–1244. https://doi.org/10.1016/0043-1354(90)90047-A

Shah KA, Joshi GS (2017) Evaluation of water quality index for River Sabarmati, Gujarat, India. Appl Water Sci 7(3):1349–1358. https://doi.org/10.1007/s13201-015-0318-7

Said A, Stevens DK, Sehlke G (2004) An innovative index for evaluating water quality in streams. Environ Manage 34(3):406–414. https://doi.org/10.1007/s00267-004-0210-y

Adimalla N, Qian H, Li P (2019) Entropy water quality index and probabilistic health risk assessment from geochemistry of groundwaters in hard rock terrain of Nanganur County, South India. Geochemistry 80(4):125544. https://doi.org/10.1016/j.chemer.2019.125544

Long Y, Yang Y, Lei X, Tian Y, Li Y (2019) Integrated assessment method of emergency plan for sudden water pollution accidents based on improved TOPSIS, Shannon entropy and a coordinated development degree model. Sustainability 11(2):510. https://doi.org/10.1007/s12403-019-00299-8

Yang Z, Wang Y (2020) The cloud model based stochastic multi-criteria decision making technology for river health assessment under multiple uncertainties. J Hydrol 581:124437. https://doi.org/10.1016/j.jhydrol.2019.124437

Hanoon MS, Ahmed AN, Fai CM, Birima AH, Razzaq A, Sherif M, Sefelnasr A, El-Shafie A (2021) Application of artificial intelligence models for modeling water quality in groundwater: comprehensive review, evaluation and future trends. Water Air Soil Pollut 232(10):1–41. https://doi.org/10.1007/s11270-021-05311-z

Chanapathi T, Thatikonda S (2019) Fuzzy-based regional water quality index for surface water quality assessment. J Hazard Toxic Radioact Waste 23(4):4019010. https://doi.org/10.1061/(asce)hz.2153-5515.0000443

Hamdan ANA, Al Saad ZAA, Abu-Alhail S (2021) Fuzzy system modelling to assess water quality for irrigation purposes. J Water Land Dev 50:98–107. https://doi.org/10.24425/jwld.2021.138165

Hue NH, Thanh NH (2020) Surface water quality analysis using Fuzzy logic approach: a case of inter-provincial irrigation network in Vietnam. IOP Conf Ser: Earth Environ Sci 527(1):12017. https://doi.org/10.1088/1755-1315/527/1/012017

Lindang HU, Tarmudi ZH, Jawan A (2017) Assessing water quality index in river basin: Fuzzy inference system approach. Malays J Geosci 1(1):27–31. https://doi.org/10.1007/s12403-019-00299-8

Sharifi H, Roozbahani A, Shahdany SMH (2021) Evaluating the performance of agricultural water distribution systems using FIS, ANN and ANFIS intelligent models. Water Resour Manage 35(6):1797–1816

Selvaraj A, Saravanan S, Jennifer JJ (2020) Mamdani fuzzy based decision support system for prediction of groundwater quality: an application of soft computing in water resources. Environ Sci Pollut Res 27(20):25535–25552. https://doi.org/10.1007/s11356-020-08803-3

Hajji S, Yahyaoui N, Bousnina S, Ben Brahim F, Allouche N, Faiedh H, Bouri S, Hachicha W, Aljuaid AM (2021) Using a Mamdani Fuzzy Inference System Model (MFISM) for ranking groundwater quality in an agri-environmental context: case of the Hammamet-Nabeul shallow aquifer (Tunisia). Water 13(18):2507. https://doi.org/10.3390/w13182507

Kambalimath S, Deka PC (2020) A basic review of fuzzy logic applications in hydrology and water resources. Appl Water Sci 10(8):191. https://doi.org/10.1007/s13201-020-01276-2

Islam AR, Al Mamun A, Rahman MM, Zahid A (2020) Simultaneous comparison of modified-integrated water quality and entropy weighted indices: implication for safe drinking water in the coastal region of Bangladesh. Ecol Indic 113:106229. https://doi.org/10.1016/j.ecolind.2020.106229

Rabeiy RES (2018) Assessment and modeling of groundwater quality using WQI and GIS in Upper Egypt area. Environ Sci Pollut Res 25(31):30808–30817. https://doi.org/10.1007/s11356-017-8617-1

Uddin MG, Olbert AI, Nash S (2020) Assessment of water quality using water quality index (WQI). CERI 2020 Proc 85:966–982

Google Scholar  

Talat RA, Al-Assaf AYR, Al-Saffawi AYT (2019) Valuation of water quality for drinking and domestic purposes using WQI : a case study for groundwater of Al-Gameaa and Al-Zeraee quarters in Mosul city/Iraq. J Phys: Conf Ser 1294(7). https://doi.org/10.1088/1742-6596/1294/7/072011

Kachroud M, Trolard F, Kefi M, Jebari S, Bourrié G (2019) Water quality indices: challenges and application limits in the literature. Water 11(2):361. https://doi.org/10.3390/w11020361

Fathi E, Zamani-Ahmadmahmoodi R, Zare-Bidaki R (2018) Water quality evaluation using water quality index and multivariate methods, Beheshtabad River, Iran. Appl Water Sci 8(7):1–6. https://doi.org/10.1007/s13201-018-0859-7

Feng Y, Bao Q, Chenglin L, Bowen W, Zhang Y (2018) Introducing biological indicators into CCME WQI using variable fuzzy set method. Water Resour Manage 32(8):2901–2915. https://doi.org/10.1007/s13201-018-0859-7

Gikas GD, Sylaios GK, Tsihrintzis VA, Konstantinou IK, Albanis T, Boskidis I (2020) Comparative evaluation of river chemical status based on WFD methodology and CCME water quality index. Sci Total Environ 745:140849. https://doi.org/10.1016/j.scitotenv.2020.140849

Ott WR (1978) Environmental indices: theory and practice. Ann Arbor Science Publishers, Inc., Ann Arbor, MI. https://www.osti.gov/biblio/6681348 . Accessed 13 Nov 2021

Ismail AH, Robescu D (2019) Assessment of water quality of the Danube river using water quality indices technique. Environ Eng Manag J 18(8):1727–1737. https://doi.org/10.30638/eemj.2019.163

Khan Y, Chai SS (2017) Ensemble of ANN and ANFIS for water quality prediction and analysis-a data driven approach. J Telecommun Electron Comput Eng (JTEC) 9(29):117–122

CAS   Google Scholar  

Patki VK, Jahagirdar S, Patil YM, Karale R, Nadagouda A (2021). Prediction of water quality in municipal distribution system. Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2021.02.826

Volodina V, Challenor P (2021) The importance of uncertainty quantification in model reproducibility. Phil Trans R Soc A 379(2197):20200071. https://doi.org/10.1098/rsta.2020.0071

Rodrigues C, Cunha MÂ (2017) Assessment of the microbiological quality of recreational waters: indicators and methods. Euro-Mediterr J Environ Integr 2(1):1–18. https://doi.org/10.1007/s41207-017-0035-8

Heiß L, Bouchaou L, Tadoumant S, Reichert B (2020) Index-based groundwater vulnerability and water quality assessment in the arid region of Tata city (Morocco). Groundw Sustain Dev 10:100344. https://doi.org/10.1016/j.gsd.2020.100344

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Acknowledgements

The authors are thankful to Vidyasagar University for providing good research environment.

The authors state that they did not receive any funding, grants, or other forms of support in the development of this paper.

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Centre for Environmental Studies, Vidyasagar University, Midnapore, 721102, India

Atanu Manna

Department of Business Administration, Vidyasagar University, Midnapore, West Bengal, 721102, India

Debasish Biswas

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The study’s conception and design were aided by all of the authors. The first author [Atanu Manna] conducted the literature search and data presentation in this review article, which was drafted and critically revised by the corresponding author [Dr. Debasish Biswas].

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Manna, A., Biswas, D. Assessment of Drinking Water Quality Using Water Quality Index: A Review. Water Conserv Sci Eng 8 , 6 (2023). https://doi.org/10.1007/s41101-023-00185-0

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• Published: 11 April 2022

Water quality assessment and evaluation of human health risk of drinking water from source to point of use at Thulamela municipality, Limpopo Province

• N. Luvhimbi 1 ,
• T. G. Tshitangano 1 ,
• J. T. Mabunda 1 ,
• F. C. Olaniyi 1 &
• J. N. Edokpayi 2  

Scientific Reports volume  12 , Article number:  6059 ( 2022 ) Cite this article

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Water quality has been linked to health outcomes across the world. This study evaluated the physico-chemical and bacteriological quality of drinking water supplied by the municipality from source to the point of use at Thulamela municipality, Limpopo Province, South Africa; assessed the community practices regarding collection and storage of water and determined the human health risks associated with consumption of the water. Assessment of water quality was carried out on 114 samples. Questionnaires were used to determine the community’s practices of water transportation from source to the point-of-use and storage activities. Many of the households reported constant water supply interruptions and the majority (92.2%) do not treat their water before use. While E. coli and total coliform were not detected in the water samples at source (dam), most of the samples from the street taps and at the point of use (household storage containers) were found to be contaminated with high levels of E. coli and total coliform. The levels of E. coli and total coliform detected during the wet season were higher than the levels detected during the dry season. Trace metals’ levels in the drinking water samples were within permissible range of both the South African National Standards and World Health Organisation. The calculated non-carcinogenic effects using hazard quotient toxicity potential and cumulative hazard index of drinking water through ingestion and dermal pathways were less than unity, implying that consumption of the water could pose no significant non-carcinogenic health risk. Intermittent interruption in municipal water supply and certain water transportation and storage practices by community members increase the risk of water contamination. We recommend a more consistent supply of treated municipal water in Limpopo province and training of residents on hygienic practices of transportation and storage of drinking water from the source to the point of use.

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Introduction.

Water is among the major essential resources for the sustenance of humans, agriculture and industry. Social and economic progress are based and sustained upon this pre-eminent resource 1 . Availability and easy access to safe and quality water is a fundamental human right 2 and availability of clean water and sanitation for all has been listed as one of the goals to be achieved by the year 2030 for sustainable development by the United Nations General Assembly (UNGA) 3 .

The physical, chemical, biological and aesthetic properties of water are the parameters used to describe its quality and determine its capability for a variety of uses including the protection of human health and the aquatic ecosystem. Most of these properties are influenced by constituents that are either dissolved or suspended in water and water quality can be influenced by both natural processes and human activities 4 , 5 . The capacity of a population to safeguard sustainable access to adequate quantities and acceptable quality of water for sustaining livelihoods of human well-being and socioeconomic growth; as well as ensuring protection against pollution and water related disasters; and for conserving ecosystems in a climate of peace and political balance is regarded to as water security 6 .

Although the world’s multitudes have access to water, in numerous places, the available water is seldom safe for human drinking and not obtainable in sufficient quantities to meet basic health needs 7 . The World Health Organization (WHO) estimated that about 1.1 billion people globally drink unsafe water and most diarrheal diseases in the world (88%) is attributed to unsafe water, poor sanitation and unhygienic practices. In addition, the water supply sector is facing enormous challenges due to climate change, global warming and urbanization. Insufficient quantity and poor quality of water have serious impact on sustainable development, especially in developing countries 8 .

The quality of water supplied by the municipality is to be measured against the national standards for drinking water developed by the federal governments and other relevant bodies 9 . These standards considered some attributes to be of primary importance to the quality of drinking water, while others are considered to be of secondary importance. Generally, the guidelines for drinking water quality recommend that faecal indicator bacteria (FIB), especially Escherichia coli ( E. coli ) or thermo tolerant coliform (TTC), should not be found in any 100 mL of drinking water sample 8 .

Despite the availability of these standards and guidelines, numerous WHO and United Nations International Children Emergency Fund (UNICEF) reports have documented faecal contamination of drinking water sources, including enhanced sources of drinking water like the pipe water, especially in low-income countries 10 . Water-related diseases remain the primary cause of a high mortality rate for children under the age of five years worldwide. These problems are specifically seen in rural areas of developing countries. In addition, emerging contaminants and disinfection by-products have been associated with chronic health problems for people in both developed and developing countries 11 . Efforts by governmental and non-governmental organizations to ensure water security and safety in recent years have failed in many areas due to a lack of sustainability of water supply infrastructures 12 .

Water quality, especially regarding the microbiological content, can be compromised during collection, transport, and home storage. Possible sources of drinking water contamination are open field defecation, animal wastes, economic activities (agricultural, industrial and businesses), wastes from residential areas as well as flooding. Any water source, especially is vulnerable to such contamination 13 . Thus, access to a safe source alone does not ensure the quality of water that is consumed, and a good water source alone does not automatically translate to full health benefits in the absence of improved water storage and sanitation 14 . In developing countries, it has been observed that drinking-water frequently becomes re-contaminated following its collection and during storage in homes 15 .

Previous studies in developing countries have identified a progressive contamination of drinking water samples with E. coli and total coliforms from source to the point of use in the households, especially as a result of using dirty containers for collection and storage processes 16 , 17 , 18 . Also, the type of water treatment method employed at household levels, the type of container used to store drinking water, the number of days of water storage, inadequate knowledge and a lack of personal and domestic hygiene have all been linked with levels of water contamination in households 19 , 20 .

In South Africa, many communities have access to treated water supplied by the government. However, the water is more likely to be piped into individual households in the urban than rural areas. In many rural communities, the water is provided through the street taps and residents have to collect from those taps and transport the water to their households. Also, water supply interruptions are frequently experienced in rural communities, hence, the need for long-term water storage. A previous study of water quality in South Africa reported better quality of water at source than the water samples obtained from the household storage containers, showing that water could be contaminated in the process of transporting it from source to the point of use 21 .

This study was conducted in a rural community at Thulamela Municipality, Limpopo province, South Africa, to describe the community’s drinking water handling practices from source to the point of use in the households and evaluate the quality of the water from source (the reservoir), main distribution systems (street taps), yard connections (household taps) and at the point of use (household storage containers). Water quality assessment was done by assessing the microbial contamination and trace metal concentrations, and the possible health risks due to exposure of humans to the harmful pathogens and trace metals in the drinking water were determined.

The study was conducted at Lufule village in Thulamela municipality, Limpopo Province, South Africa. The municipality is situated in the eastern subtropical region of the province. The province is generally hot and humid and it receives much of its rainfall during summer (October–March) 22 . Lufule village is made up of 386 households and a total population of 1, 617 residents 23 . The study area includes Nandoni Dam (main reservoir) which acquires its raw water from Luvuvhu river that flows through Mutoti and Ha-Budeli villages just a few kilometers away from Thohoyandou town. Nandoni dam is where purification process takes place to ensure that the water meets the standards set for drinking water. This dam is the main source of water around the municipality, and it is the one which supplies water to selected areas around the dam, including Lufule village. Water samples for analysis were collected from the dam (D), street taps (ST), household taps (HT) and household storage containers (HSC) (Fig.  1 ).

Map of the study area showing water samples’ collection areas.

Research design

This study adopted a quantitative design comprising of field survey and water analysis.

Field survey

The survey was done to identify the selected households and their shared source of drinking water (street taps). The village was divided into 10 quadrants for sampling purposes. From each quadrant, 6 households were randomly selected where questionnaires were distributed and household water samples were also collected for analysis.

Quantitative data collection

A structured interviewer-administered questionnaire was employed for data collection in the selected households. The population of Lufule village residents aged 15–69 years is 1, 026 (Census, 2011). About 10% of the adult population (~ 103) was selected to complete the questionnaires to represent the entire population. However, a total of 120 questionnaires were distributed, to take care of those which might be lacking vital information and therefore would not qualify to be analysed. Adults between the ages of 18 and 69 years were randomly selected to complete the questionnaire which includes questions concerning demographic and socio-economic statuses of the respondents, water use practices, sanitation, hygiene practices as well as perception of water quality and health. The face validity of the instrument was ensured by experts in the Department of Public Health, University of Venda, who reviewed questionnaire and confirmed that the items measure the concepts of interest relevant to the study 24 . Respondents were given time to go through the questionnaire and the researcher was present to clear any misunderstanding that may arise.

Water sampling

Permission to collect water samples from the reservoir tank at the Nandoni water treatment plant and households was obtained from the plant manager and the households’ heads respectively. Two sampling sites were identified at the dam, from where a water sample each was collected during the dry and the wet season. Similarly, 8 sampling sites were identified from the street and household taps, while 60 sampling sites were targeted for the household storage containers. However, only 39 household sites were accessible for sample collection, due to unavailability of the residents at the times of the researcher’s visit. Thus, water samples were collected from a total of 57 sites. Samples were collected from each of the sites during the dry (12th–20th April, 2019) and wet seasons (9th–12th December, 2019) between the hours of 08h00 and 14h30. A total of 114 samples were collected during the sampling period: 4 from the reservoir, 16 from street taps, 16 from household taps and 78 from households’ storage systems. Water samples were collected in 500 mL sterile polyethylene bottles. After collection, the containers were transported to the laboratory on ice in a cooler box. Each of the samples was tested for physico-chemical parameters, microbial parameters and trace metals’ concentration.

Physicochemical parameters’ analysis

Onsite analysis of temperature, pH, Electrical conductivity (EC) and Total Dissolved Solids (TDS) were performed immediately after sampling using a multimeter (model HI “HANNA” instruments), following the standards protocols and methods of American Public Health Association (APHA) 25 . The instrument was calibrated in accordance with the manufacturer’s guideline before taking the measurements. The value of each sample was taken after submerging the probe in the water and held for a couple of minutes to achieve a reliable reading. After measurement of each sample, the probe was rinsed with de-ionized water to avoid cross contamination among different samples.

ICP-OES and ICP-MS analyses of major and trace elements

An inductively coupled plasma optical emission spectrophotometer (ICP-OES) was used to analyse the major metals (Calcium (Ca), Sodium (Na), Potassium (K) and Magnesium (Mg)) in the water samples while inductively coupled plasma mass spectrophotometer (ICP-MS) was used to analyze the trace metals. The instrument was standardized with a multi-element calibration standard IV for ICP for Copper (Cu), Manganese (Mn), Iron (Fe), Chromium (Cr), Cadmium (Cd), Arsenic (As), Nickel (Ni), Zinc (Zn), Lead (Pb) and Cobalt (Co) and analytical precision was checked by frequently analysing the standards as well as blanks. ICP multi Standard solution of 1000 ppm for K, Ca, Mg and Na was prepared with NH 4 OAC for analysis to verify the accuracy of the calibration of the instrument and quantification of selected metals before sample analysis, as well as throughout the analysis to monitor drift.

Microbiological water quality analysis

Analysis of microbial parameters was conducted within 6 h of collection as recommended by APHA 25 . Viable Total coliform and E. coli were quantified in each sample using the IDEXX technique approved by the United States Environmental Protection Agency (USEPA). Colilert media was added to 100 mL sample and mixed until dissolved completely. The solution was poured into an IDEXX Quanti-Tray/2000 and sealed using the Quanti-Tray sealer 26 . The samples were incubated at 35 °C for 24 h. Trays were scanned using a fluorescent UV lamp to count fluorescent wells positive for E. coli concentration and counted with the most probable number (MPN) table provided by the manufacturer 27 .

Health risk assessment

Risk assessment have been estimated for ingestion and dermal pathways. Exposure pathway to water for ingestion and dermal routes are calculated using Eqs. ( 1 ) and ( 2 ) below:

where Exp ing : exposure dose through ingestion of water (mg/kg/day); BW: average body weight (70 kg for adults; 15 kg for children); Exp derm : exposure dose through dermal absorption (mg/kg/day); C water : average concentration of the estimated metals in water (μg/L); IR: ingestion rate in this study (2.0 L/day for adults; 1.0 L/day for children); ED: exposure duration (70 years for adults; and 6 years for children);AT: averaging time (25,550 days for an adult; 2190 days for a child); EF: exposure frequency (365 days/year) SA: exposed skin area (18.000 cm 2 for adults; 6600 cm 2 for children); K p : dermal permeability coefficient in water, (cm/h), 0.001 for Cu, Mn, Fe and Cd, while 0.0006 for Zn; 0.002 for Cr and 0.004 for Pb; ET: exposure time (0.58 h/ day for adults; 1 h/day for children) and CF: unit conversion factor (0.001 L/cm 3 ) 28 .

The hazard quotient (HQ) of non-carcinogenic risk by ingestion pathway can be determined by Eq. ( 3 )

where RfD ing is ingestion toxicity reference dose (mg/kg/day). An HQ under 1 is assumed to be safe and taken as significant non-carcinogenic, but HQ value above 1 may indicate a major potential health concern associated with over-exposure of humans to the contaminants 28 .

The total non-carcinogenic risk is represented by hazard index (HI). HI < 1 means the non-carcinogenic risk is acceptable, while HI > 1 indicates the risk is beyond the acceptable level 29 . The HI of a given pollutant through multiple pathways can be calculated by summing the hazard quotients by Eq. ( 4 ) below.

Carcinogenic risks for ingestion pathway is calculated by Eq. ( 5 ). For the selected metals in the study, carcinogenic risk (CR ing ) can be defined as the probability that an individual will develop cancer during his lifetime due to exposure under specific scenarios 30 .

where CRing is carcinogenic risk via ingestion route and SF ing is the carcinogenic slope factor.

Data analysis

Data obtained from the survey were analysed using Microsoft Excel and presented as descriptive statistics in the form of tables and graphs. The experimental data obtained was compared with the South African National Standards (SANS) 31 and Department of Water Affairs and Forestry (DWAF) 32 guidelines for domestic water use.

Ethics approval and consent to participate

The ethical clearance for this study was granted by the University of Venda Health, Safety and Research Ethics’ Committee (SHS/19/PH/14/1104). Permission to conduct the study was obtained from the Department of Water affairs, Limpopo province, Vhembe district Municipality and the selected households. Respondents were duly informed about the study and informed consent was obtained from all of them. The basic ethical principles of voluntary participation, informed consent, anonymity and confidentiality of respondents were duly complied with during data collection, analysis and reporting.

Consent for publication

Not applicable.

Socio-demographic characteristics of respondents

A total of 120 questionnaires were distributed but only 115 were completed, making a good response rate of 95%. The socio-demographic characteristics of the respondents are presented in Table 1 .

Household water supply

Many households (68.7%) had their primary water source from the municipality piped into their yards, but only 5.2% have the water flowing within their houses. The others have to fetch water at their neighbours’ yards or use the public taps on the streets. When the primary water supply is interrupted (i.e. when there is no water flowing through the pipes within the houses, yards or the public taps due to water rationing activities by the municipality, leakage of water distribution pipes, vandalization of pipes during road maintenance, etc.), the interruption usually lasts between a week or two, during which the respondents resort to other alternative sources. A return trip to the secondary source of water usually takes between 10 and 30 min for more than half of the respondents (53.0%) (Table 2 ).

Water storage and treatment practices at the household

Household water was most frequently stored in plastic buckets (n = 78, 67.8%), but ceramic vessels, metal buckets and other containers are also used for water storage (Fig.  2 ). Most households reported that their drinking water containers were covered (n = 111, 96.5%). More than half (53.9%) of the respondents used cups with handles to collect water from the storage containers whereas 37.4% used cups with no handles. Only 7.8% households reported that they treat their water before use mainly by boiling. Approximately 82.6% of respondent are of the opinion that one cannot get sick from drinking water and only 17.4% knew the risks that come with untreated water, and cited diarrhoea, schistosomiasis, cholera, fever, vomiting, ear infections, malnutrition, rash, flu and malaria as specific illnesses associated with water. Despite these perceptions, the majority (76.5%) were satisfied with their current water source. The few (23.5%) who were not satisfied cited poor quality, uncleanness, cloudiness, bad odour and taste in the water as reasons for their dissatisfaction (Table 3 ).

Examples of household water storage containers, some with lids and others without lids (photo from fieldwork).

Sanitation practices at the household level

More than half of the respondents (67%) use pit toilets, whereas only 26.1% use the flush to septic tank system, most of the toilets (93.9%) have a concrete floor. About 76.5% of households do not have designated place to wash their hands, however, all respondents indicated that they always wash their hands with soap or any of its other alternatives before preparing meals and after using the toilet (Table 4 ).

Water samples analysis

The water samples analyses comprise of microbial analysis, physico-chemical analysis and trace metals' parameters.

Microbial analysis

The samples from the reservoir during dry and wet season had 0 MPN/100 mL of total coliform and E. coli and were within the recommended limits of WHO and SANS for drinking water. During the wet season, seven out of the eight water samples collected from the street taps were contaminated with total coliform, while four of the samples taken from the same source were contaminated with total coliform during the dry season. Water samples from street taps 3 and 7 (ST 3 and ST7) were contaminated with total coliform during both seasons, however, the total coliform counts during the wet season were more than the counts during the dry season. None of the samples was contaminated with E. coli during the dry season, however, 2 samples from the street taps (ST3 & ST6) were found to be contaminated with E. coli during the wet season. Samples from household taps showed a similar trend with the street taps—with all samples being contaminated with total coliform during the wet season. Though 7 of the 8 samples taken from the household taps were contaminated with total coliform during the dry season, the samples from the same sources showed a higher level of total coliform in the wet season, with almost all the samples showing contamination at maximum detection levels of more than 2000 MPN/100 mL, except one sample (HT8) which showed a higher level of contamination with total coliform during the dry compared with the wet season. Only one sample (HT4) was found to be contaminated with E. coli during both dry and wet season. This shows that total coliform contamination levels are higher during the wet season than the dry season (Table 5 ).

Water samples from household storage containers (HSC) showed a higher level of total coliform during the wet season than the dry season and more samples were contaminated with E. coli during the wet season also (Table 6 ). A higher level of contamination was recorded for the HSCs compared to the street and household taps.

Physico-chemical analysis

In the reservoir samples, the pH value ranged from 8.37 to 8.45, EC ranged between 183 and 259 µS/cm whereas TDS varied between 118 and 168 mg/L. Similarly, in the street tap samples, pH value ranged from 7.28 and 9.33, EC ranged between 26 and 867 µS/cm whereas TDS varied between 16 and 562 mg/L (Fig.  3 ).

EC and TDS levels for the street taps and reservoir samples.

In the household taps, pH value ranged from 7.70–9.98, EC range between 28–895 µS/cm and TDS varied between 18 and 572 mg/L (Fig.  4 ).

EC and TDS levels for household taps.

In household storage container samples, the pH value ranges from 7.67–9.77, EC ranged between 19–903 µS/cm and TDS values ranged from 12–1148 mg/L (Fig.  5 ).

EC and TDS levels for household storage container samples.

Analysis of cations and trace metals in water

To detect the cations’ and trace metals’ concentrations in the water samples, representative samples from each of the sources were selected for analysis. The concentration of Calcium ranged between 2.14 and 31.65 mg/L, Potassium concentration ranged from 0.14 to 1.85 mg/L, Magnesium concentration varied from 1.32 to 16.59 mg/L, Sodium ranged from 0.18 to 12.96 mg/L (Table 7 ).

Trace metals’ analysis

The minimum and maximum concentrations of trace metals (Al, Mn, Fe, Co, Ni, Cu, Zn, As and Pb) present in water samples from selected street taps, household taps and household storage containers are presented in Table 8 .

Hazard quotient (HQ) and carcinogenic risk assessment

Table 9 presents the exposure dosage and hazard quotient (HQ) for ingestion and dermal pathway for metals. The HQ ing and HQ derm for all analyzed trace metals in both children and adults were less than one unit, indicating that there are no potential non-carcinogenic health risks associated with consumption of the water. Table 10 presents the total Hazard Quotient and Health risk index (HI) for trace metals in the water samples, showing that residents of the study area are not susceptible to non-cancer risks due to exposure to trace metals in drinking water. Table 11 presents the cancer risk associated with the levels of Ni, As and Pb in the drinking water samples. The table shows that only the maximum levels of lead had the highest chance of cancer risks for both adults and children.

This study provides information about the quality of drinking water in a selected rural community of Thulamela municipality of Limpopo province, South Africa, taking into consideration the physicochemical, microbiological and trace metals’ parameters of the treated water supplied to the village by the government, through the municipality. Many participants in the study have their primary source of water piped into their yards, while very few have water in their houses. This implies that getting water for household use would involve collecting the water from the yard and then into the storage containers. Those who do not have the taps in their yards have to collect water from the neighbours’ yards or the street taps. This observation is not restricted to the study area, as a similar situation has been observed in other rural communities of Limpopo Province 21 . This need to pass water through multiple containers before the point of use increases the risk of contamination.

Residents of the study area, just like residents of other settlements in Thulamela Municipality 21 , store their drinking water in plastic buckets, ceramic vessels, jerry cans and other containers. Almost all the respondents (96.5%) claim that their water storage vessels are covered and that their drinking water usually stays for less than a week in the storage containers (87.8%). Covering of water storage containers reduces the risk of water contamination from dust or other airborne particles. However, intermittent interruption of municipal water supply lasting for a week or more in the study area and the consequent use of alternative sources of water predispose the residents to various health risks as intermittent interruption in water supply has been linked to higher chances of contamination in the distribution systems, compared with continuous supply; in addition, the alternative sources of water may not be of a good quality as the treated municipal water 33 , 34 , yet, more than half of the respondents in this study (53%) use water directly from source without any form of treatment. This is because many residents in rural communities of Limpopo province believe that the water they drink is of good quality and thus do not need any further treatment 21 . The few who treat their water before drinking mostly use the boiling method. While boiling and other home-based interventions like solar disinfection of water have been reported to improve the quality of drinking water; drinking vessels, like cups, have also been implicated in water re-contamination of treated water at the point of use 16 and most respondents (91.3%) in this study admittedly use cups to collect water from the storage containers. The risk of contamination is even increased when cups without handles are used, where there is a higher chance that the water collector would touch the water in the container with his/her fingers. The Centres for Disease Control and Prevention (CDC) recommends that containers for drinking water should be fitted with a small opening with a cover or a spigot, through which water can be collected while the container remains closed, without dipping any potentially contaminated object into the container 35 . However, it is noteworthy that all the respondents claim to always wash their hands with soap (or its equivalents) and water after using the toilets, a constant practice of hand washing after using the toilet has been associated with a reduced risk of water contamination with E. coli 19 .

Treated water from the dam tested negative for both total coliform and E. coli hence complied with regulatory standards of SANS 31 and WHO 8 . The results could probably be due to the use of chlorine as a disinfectant in the treatment plant. Using disinfectants, pathogenic bacteria from the water can be killed and water made safe for the user. Similar studies have also reported that treated water in urban water treatment plants contains no total coliforms and E. coli 36 . In contrast, treated water sources in rural areas have been reported to have considerable levels of total coliform and E. coli 37 . The reason alluded to this include lack of disinfectant, no residual chlorine in the treated water, high prevalence of open defecation and unhygienic practices in proximity to water sources 38 .

From the water samples collected from the street taps, 62.5% were found to be contaminated with total coliform during the dry season, while the percentage rose to 87.5% during the wet season. The street tap which is about 13 km from the reservoir recorded high levels of total coliform ranging from 1.0 -2000 MPN/100 mL with most of the sites exceeding the WHO guidelines of 10 MPN/100 mL 8 . In both seasons, all the samples tested negative for E. coli , this complies with the WHO guideline of 0 MPN/100 mL. While the water leaving the treatment plant met bacteriological standards, the detection of coliform bacteria in the distribution lines suggest that the water is contaminated in the distribution networks. This could be due to the adherence of bacteria onto biofilms or accidental point source contamination by broken pipes, installation and repair works 39 . Furthermore, the water samples from households’ storage containers were contaminated by total coliform (73% and 85%) and E. coli (10.4% and 13.2%) during the dry and wet season, respectively. Microbiological contamination of household water stored in containers could be due to unhygienic practices occurring between the collection point and the point-of-use 40 , 41 .

Generally, higher levels of contamination were recorded in the wet season than in the dry season. The wet season in Thulamela Municipality is often characterized with increased temperature which could lead to favourable condition for microbial growth. Also, the treatment plant usually makes use of the same amount of chlorine for water purification during both seasons, even though influent water would be of a higher turbidity during the wet season, hence reducing the levels of residual chlorine 42 .

The pH of the analyzed samples from the study area ranged from 7.15 to 9.92. Most of the samples were within the values recommended by SANS (5 to 9.7) and comparable to results from previous similar studies 31 , 43 . Also, the electrical conductivity of all water samples from this study ranged from 28 µS/cm to 903 µS/cm which complied with the recommended value of SANS: < 1700 µS/cm 31 . The presence of dissolved solids such as calcium, chloride, and magnesium in water samples is responsible for its electrical conductivity 44 .

Total dissolved solids are the inorganic salts and small amounts of organic substance, which are present as solution in water 45 . Water has the ability to dissolve a wide range of inorganic and some organic minerals or salts such as potassium, calcium, sodium, bicarbonates, chlorides, magnesium, sulphates, etc. These minerals produced unwanted taste and colour in water 46 . A high TDS value indicates that water is highly mineralised. The recommended TDS value set for drinking water quality is ≤ 1200 mg/L 31 . In this study, the TDS values ranged from 18 mg/L to 572 mg/L. Hence, the TDS of all the household’s storage samples complied with the guidelines and consistent with previous studies 47 .

The analysis of magnesium (1.32 to 16.59 mg/L) and calcium (2.14 to 31.65 mg/L) concentrations showed that they were within the permissible range recommended for drinking water by SANS 31 and WHO 8 . All living organisms depend on magnesium in all types of cells, body tissues and organs for variety of functions while calcium is very important for human cell physiology and bones. Similar studies in Ethiopia and Turkey also showed acceptable levels of these metals in drinking water 46 , 48 . Likewise, the levels of potassium (0.14 to 1.85 mg/L) and sodium (0.18 to 12.96 mg/L) were within the permissible limit of WHO and SANS and may not cause health related problems. Sodium is essential in humans for the regulation of body fluid and electrolytes, and for proper functioning of the nerves and muscles, however, excessive sodium in the body can increase the risk of developing a high blood pressure, cardiovascular diseases and kidney damage 49 , 50 . Potassium is very important for protein synthesis and carbohydrate metabolism, thus, it is very important for normal growth and body building in humans, but, excessive quantity of potassium in the body (hyperkalemia) is characterized with irritability, decreased urine production and cardiac arrest 51 .

Metals like copper (Cu), cobalt (Co) and zinc (Zn) are essential requirements for normal body growth and functions of living organisms, however, in high concentrations, they are considered highly toxic for human and aquatic life 42 . Elevated trace metal(loids) concentrations could deteriorate water quality and pose significant health risks to the public due to their toxicity, persistence, and bio accumulative nature 52 . In this study, the concentrations of Manganese, Cobalt, Nickel and Copper all complied with the recommended concentration by SANS for domestic water use.

Aluminum concentration in the drinking water samples ranged from 1.25—13.46 µg/L. All analysed samples complied with the recommended concentration of ≤ 300 µg/L for domestic water use 31 . The recorded levels of Al in water from this study should not pose any health risk. At a high concentration, aluminium affects the nervous system, and it is linked to several diseases, such as Parkinson’s and Alzheimer’s diseases 53 . Iron (Fe) is an essential element for human health, required for the production of protein haemoglobin, which carries oxygen from our lungs to the other parts of the body. Insufficient or excess levels of iron can have negative effect on body functions 54 . The recommended concentration of iron in drinking water is ≤ 2000 µg/L 31 . In this study, the concentration of iron in the samples ranged from 0.96 to 73.53 µg/L. Similar results were reported by Jamshaid et al. in Khyber Pakhtunkhwa province 55 . A high concentration of Fe in water can give water a metallic taste, even though it is still safe to drink 56 .

The levels of Pb, As and Zn were in the range of 0.02–0.57 µg/L, 0.02–0.17 µg/L, and 2.54–194.96 µg/L, respectively whereas Cr was not detected in the samples collected. The levels recorded complied with the SANS 31 and WHO 8 guidelines for drinking water. Similar results were reported by Mohod and Dhote 57 . Lead is not desirable in drinking water because it is carcinogenic and can cause growth impairment in children 41 . Inorganic arsenic is a confirmed carcinogen and is the most significant chemical contaminant in drinking-water globally 44 . Zinc deficiency can cause loss of appetite, decreased sense of taste and smell, slow wound healing and skin sores 58 . Cr is desirable at low concentration but can be harmful if present in elevated levels.

The hazard quotient (HQ) takes into consideration the oral toxicity reference dose for a trace metal that humans can be exposed to 59 . Health related risk associated with the exposure through ingestion depends on the weight, age and volume of water consumed by an individual. HQ ing and HQ derm for all analyzed trace metals in both children and adults were less than one unit (Table 9 ), indicating that there are no potential non-carcinogenic health risks associated with the consumption of the water from the study area either by children or adults. The calculated average cumulative health risk index (HI) for children and adult was 3.88E-02 and 1.78E-02, respectively. HQ across metals serve as a conservative assessment tool to estimate high-end risk rather than low end-risk in order to protect the public. This served as a screen value to determine whether there is major significant health risk 60 . The results in this study signifies that the population of the investigated area are not susceptible to non-cancer risks due to exposure to trace metals in drinking water. Similar observation has been reported by Bamuwamye et al. after investigating human health risk assessment of trace metals in Kampala (Uganda) drinking water 61 . It should be noted that the hazard index values for children were higher than that of adult, suggesting that children were more susceptible to non-carcinogenic risk from the trace metals.

Drinking water with trace metals such as Pb, As, Cr and Cd could potentially enhance the risk of cancer in human beings 62 , 63 . Long term exposure to low amounts of toxic metals might, consequently, result in many types of cancers. Using As, Ni and Pb carcinogens, the total exposure risks of the residents in Table 11 . For trace metals, an acceptable carcinogenic risk value of less than 1 × 10 −6 is considered as insignificant and the cancer risk can be neglected; while an acceptable carcinogenic risk value of above 1 × 10 –4 is considered as harmful and the cancer risk is worrisome. Amongst the studied trace metals, only the maximum levels of lead for both adults and children had the highest chance of cancer risks (1.93E−03 and 4.46E−03) while Arsenic and Nickel have no chance of cancer risk with values of 3.34E−06; 7.72E−06 and 2.24E−05; 5.18E−05, in both adults and children respectively. The only cancer risk to residents of the studied area could be from the cumulative ingestion of lead in their drinking water. The levels of Pb recorded in this study complied to the SANS guideline value for safe drinking water. While the levels of Pb from the dam and the street pipes were relatively low, higher levels where recorded at household taps and storage containers and this may be due to the kind of storage containers and pipes used in those households. Generally, the water supply is of low Pb levels which should not pose any health risk to the consumers. However, the residents in rural areas should be properly educated on the kind of materials to be used for safe storage of water which should not pose an additional health burden. The likelihood of cancer risk was only associated with the consumption of the highest levels of Pb reported for a life time for adults (set at 70 years) and 6 years for children. Consistent consumption of water from the same source throughout an adult’s lifetime is unlikely as residents in those communities may change their locations at some points, hence reducing the possible risk associated with consistent exposure to the same levels of Pb.

Conclusions

The study shows that as distance increases from the treatment reservoir to distribution points, the cross-contamination rate also increases, therefore, good hygienic practices is required while transporting, storing and using water. Unhygienic handling practices at any point between collection and use contribute to the deterioration of drinking water quality.

The physicochemical, bacteriological quality and trace metals’ concentration of water samples from treated source, street taps and household storage containers were majorly within the permissible range of both WHO and SANS drinking water standards. HQ for both children and adults were less than unity, showing that the drinking water poses less significance health threat to both children and adults. Amongst the studied trace metals, only the maximum level of lead for both adults and children has the highest chance of cancer risks.

We recommend that appropriate measures should be taken to maintain residual free chlorine at the distribution points, supply of municipal treated water should be more consistent in all the rural communities of Thulamela municipality, Limpopo province and residents should be trained on hygienic practices of transportation and storage of drinking water from the source to the point of use.

Data availability

The datasets used and analysed during the current study are available from the first author on reasonable request.

Abbreviations

American Public Health Association

Centres for Disease Control and Prevention

Department of Water Affairs and Forestry

Electrical conductivity

Health risk index

Hazard quotient

Household storage containers

Household taps

Inductively coupled plasma mass spectrophotometer

Inductively coupled plasma optical emission spectrophotometer

Most probable number

South African National Standards

Street taps

Total Dissolved Solids

United Nations General Assembly

United Nations International Children Emergency Fund

United States Environmental Protection Agency

World Health Organization

Taiwo, A.M., Olujimi, O.O., Bamgbose, O. & Arowolo, T.A. Surface water quality monitoring in Nigeria: Situational analysis and future management strategy. In Water Quality Monitoring and Assessment (ed. Voudouris, K) 301–320 (IntechOpen, 2012).

Corcoran, E., et al. Sick water? The central role of wastewater management in sustainable development: A rapid response assessment. United Nations Enviromental Programme UN-HABITAT, GRID-Arendal. https://wedocs.unep.org/20.500.11822/9156 (2010).

United Nations, The 2030 Agenda and the Sustainable Development Goals: An opportunity for Latin America and the Caribbean (LC/G.2681-P/Rev.3), Santiago (2018).

Hubert, E. & Wolkersdorfer, C. Establishing a conversion factor between electrical conductivity and total dissolved solids in South African mine waters. Water S.A. 41 , 490–500 (2015).

Article   CAS   Google Scholar  

Department of Water Affairs (DWA). Groundwater Strategy. Department of Water Affairs: Pretoria, South Africa. 64 (2010).

Lu, Y., Nakicenovic, N., Visbeck, M. & Stevance, A. S. Policy: Five priorities for the UN sustainable development goals. Nature 520 , 432–433 (2015).

Article   ADS   PubMed   Google Scholar  

Shaheed, A., Orgil, J., Montgomery, M. A., Jeuland, M. A. & Brown, J. Why, “improved” water sources are not always safe. Bull. World Health Organ. 92 , 283–289 (2014).

Article   PubMed   PubMed Central   Google Scholar  

WHO. Guidelines for Drinking Water Quality 4th Edn (World Health Organization, Geneva, Switzerland, 2011). http://apps.who.int/iris/bitstream/10665/44584/1/9789241548151_eng.pdf .

Patil, P. N., Sawant, D. V. & Deshmukh, R. N. Physico-chemical parameters for testing of water—a review. Int. J. Environ. Sci. 3 , 1194–1207 (2012).

CAS   Google Scholar  

Bain, R. et al. Fecal contamination of drinking-water in low-and middle-income countries: A systematic review and meta-analysis. PLoS Med. 11 , e1001644 (2014).

Younos, T. & Grady, C.A. Potable water, emerging global problems and solutions. In The Handbook of Environmental Chemistry 30 (2014).

Tigabu, A. D., Nicholson, C. F., Collick, A. S. & Steenhuis, T. S. Determinants of household participation in the management of rural water supply systems: A case from Ethiopia. Water Policy. 15 , 985–1000 (2013).

Article   Google Scholar  

Oljira, G. Investigation of drinking water quality from source to point of distribution: The case of Gimbi Town, in Oromia Regional State of Ethiopia (2015).

Clasen, T., Haller, L., Walker, D., Bartram, J. & Cairncross, S. Cost-effectiveness of water quality interventions for preventing diarrhoeal disease in developing countries. J. Water Health 5 , 599–608 (2007).

Article   PubMed   Google Scholar  

Too, J. K., Sang, W. K., Ng’ang’a, Z. & Ngayo, M. O. Fecal contamination of drinking water in Kericho District, Western Kenya: Role of source and household water handling and hygiene practices. J. Water Health 14 , 662–671 (2016).

Rufener, S., Mausezahl, D., Mosler, H. & Weingartner, R. Quality of drinking-water at source and point-of-consumption—drinking cup as a high potential recontamination risk: A field Study in Bolivia. J. Health Popul. Nutri. 28 , 34–41 (2010).

Google Scholar  

Nsubuga, F. N. W., Namutebi, E. N. & Nsubuga-ssenfuma, M. Water resources of Uganda: An assessment and review. Water Resour. Prot. 6 , 1297–1315 (2014).

Rawway, M., Kamel, M. S. & Abdul-raouf, U. M. Microbial and physico-chemical assessment of water quality of the river Nile at Assiut Governorate (Upper Egypt). J. Ecol. Health Environ. 4 , 7–14 (2016).

Agensi, A., Tibyangye, J., Tamale, A., Agwu, E. & Amongi C. Contamination potentials of household water handling and storage practices in Kirundo Subcounty, Kisoro District, Uganda. J. Environ. Public Health. Article ID 7932193, 8 pages (2019).

Mahmud, Z. H. et al. Occurrence of Escherichia coli and faecal coliforms in drinking water at source and household point-of-use in Rohingya camps, Bangladesh. Gut Pathog. 11 , 52. https://doi.org/10.1186/s13099-019-0333-6 (2019).

Edokpayi, J. N. et al. Challenges to sustainable safe drinking water: A case study of water quality and use across seasons in rural communities in Limpopo Province, South Africa. Water 10 , 159 (2018).

Article   PubMed   PubMed Central   CAS   Google Scholar  

Musyoki, A., Thifhulufhelwi, R. & Murungweni, F. M. The impact of and responses to flooding in Thulamela Municipality, Limpopo Province, South Africa, Jàmbá. J. Disaster Risk Stud. 8 , 1–10 (2016).

Census 2011. Main Place: Lufule. Accessed from Census 2011: Main Place: Lufule (adrianfrith.com) on 30/01/2022.

Bolarinwa, O. A. Principles and methods of validity and reliability testing of questionnaires used in social and health science researches. Niger. Postgrad. Med. J. 22 , 195–201 (2015).

Association, A. P. H. Standard Methods for the Examination of Water and Waste Water 16th edn. (American Public Health Association, Washington, 1992).

Bernardes, C., Bernardes, R., Zimmer, C. & Dorea, C. C. A simple off-grid incubator for microbiological water quality analysis. Water 12 , 240 (2020).

Rich CR, Sellers JM, Taylor HB, IDEXX Laboratories Inc. Chemical reagent test slide. U.S. Patent Application 29/218,589. (2006).

Naveedullah, et al. Concentrations and human health risk assessment of selected heavy metals in surface water of siling reservoir watershed in Zhejiang Province, China. Pol. J. Environ. Stud. 23 , 801–811 (2014).

Wu, J. & Sun, Z. Evaluation of shallow groundwater contamination and associated human health risk in an alluvial plain impacted by agricultural and industrial activities, mid-west China. Expos. Health. 8 , 311–329 (2016).

Wu, L., Zhang, X. & Ju, H. Amperometric glucose sensor based on catalytic reduction of dissolved oxygen at soluble carbon nanofiber. Biosens. Bioelectron. 23 , 479–484 (2007).

Article   PubMed   CAS   Google Scholar  

South African National Standard (SANS). 241-1: Drinking Water, Part 1: Microbiological, Physical, Aesthetic and Chemical Determinants. 241-2: 2015 Drinking Water, Part 2: Application of SANS 241-1 (2015).

Department of Water Affairs and Forestry (DWAF). South African Water Quality Guidelines (second edition). Volume 1: Domestic Use, (1996).

Drake, M.J. & Stimpfl, M. Water matters. In Lunar and Planetary Science Conference , Vol. 38, 1179 (2007).

Kumpel, E. & Nelson, K. L. Intermittent water supply: prevalence, practice, and microbial water quality. Environ. Sci. Technol. 50 , 542–553 (2016).

Article   ADS   CAS   PubMed   Google Scholar  

Centers for Disease Control and Prevention. The safe water system: Safe storage of drinking water. Accessed from CDC Fact Sheet on 30/01/2022 (2012).

Hashmi, I., Farooq, S. & Qaiser, S. Chlorination and water quality monitoring within a public drinking water supply in Rawalpindi Cantt (Westridge and Tench) area, Pakistan. Environ. Monit. Assess. 158 , 393–403 (2009).

Article   CAS   PubMed   Google Scholar  

Onyango, A. E., Okoth, M. W., Kunyanga, C. N. & Aliwa, B. O. Microbiological quality and contamination level of water sources in Isiolo country in Kenya. J. Environ. Public Health . 2018 , 2139867 (2018).

Gwimbi, P., George, M. & Ramphalile, M. Bacterial contamination of drinking water sources in rural villages of Mohale Basin, Lesotho: Exposures through neighbourhood sanitation and hygiene practices. Environ. Health Prev. Med. 24 , 33 (2019).

Karikari, A. Y. & Ampofo, J. A. Chlorine treatment effectiveness and physico-chemical and bacteriological characteristics of treated water supplies in distribution networks of Accra-Tema Metropolis, Ghana. Appl. Water Sci. 3 , 535–543 (2013).

Article   ADS   CAS   Google Scholar  

Thompson, T., Sobsey, M. & Bartram, J. Providing clean water, keeping water clean: An integrated approach. Int. J. Environ. Health Res. 13 , S89–S94 (2003).

Cronin, A. A., Breslin, N., Gibson, J. & Pedley, S. Monitoring source and domestic water quality in parallel with sanitary risk identification in Northern Mozambique to Prioritise protection interventions. J. Water Health 4 , 333–345 (2006).

Edokpayi, J. N., Enitan, A. M., Mutileni, N. & Odiyo, J. O. Evaluation of water quality and human risk assessment due to heavy metals in groundwater around Muledane area of Vhembe District, Limpopo Province, South Africa. Chem. Cent. J. 12 , 2 (2018).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Edimeh, P. O., Eneji, I. S., Oketunde, O. F. & Sha’Ato, R. Physico-chemical parameters and some heavy metals content of Rivers Inachalo and Niger in Idah, Kogi State. J. Chem. Soc. Nigeria 36 , 95–101 (2011).

Rahmanian, N., et al . Analysis of physiochemical parameters to evaluate the drinking water quality in the State of Perak, Malaysia. J. Chem. 1–10. Article ID 716125 (2015).

WHO/FAO. Diet, Nutrition, and the Prevention of Chronic Diseases (World Health Organisation, Geneva, 2003).

Meride, Y. & Ayenew, B. Drinking water quality assessment and its effects on resident’s health in Wondo genet campus, Ethiopia. Environ. Syst. Res. 5 , 1 (2016).

Mapoma, H. W. & Xie, X. Basement and alluvial aquifers of Malawi: An overview of groundwater quality and policies. Afr. J. Environ. Sci. Technol. 8 , 190–202 (2014).

Soylak, M., Aydin, F., Saracoglu, S., Elci, L. & Dogan, M. Chemical analysis of drinking water samples from Yozgat. Turkey Pol. J. Environ. Stud. 11 , 151–156 (2002).

Munteanu, C. & Iliuta, A. The role of sodium in the body. Balneo Res. J. 2 , 70–74 (2011).

Strazzullo, P. & Leclercq, C. Sodium. Adv. Nutr. 5 , 188–190 (2014).

Pohl, H. R., Wheeler, J. S. & Murray, H. E. Sodium and potassium in health and disease. Met. Ions Life Sci. 13 , 29–47 (2013).

Muhammad, S., Shah, M. T. & Khan, S. Health risk assessment of heavy metals and their source apportionment in drinking water of Kohistan region, northern Pakistan. Microchem. J. 98 , 334–343 (2011).

Inan-Eroglu, E. & Ayaz, A. Is aluminum exposure a risk factor for neurological disorders?. J. Res. Med. Sci. 23 , 51 (2018).

Milman, N. Prepartum anaemia: Prevention and treatment. Ann. Hematol. 87 , 949–959 (2008).

Jamshaid, M., Khan, A. A., Ahmed, K. & Saleem, M. Heavy metal in drinking water its effect on human health and its treatment techniques—a review. Int. J. Biosci. 12 , 223–240 (2018).

Tagliabue, A., Aumont, O. & Bopp, L. The impact of different external sources of iron on the global carbon cycle. Geophys. Res. Lett. 41 , 920–926 (2014).

Mohod, C. V. & Dhote, J. Review of heavy metals in drinking water and their effect on human health. Int. J. Innov. Res. Technol. Sci. Eng. 2 , 2992–2996 (2013).

Bhowmik, D., Chiranjib, K. P. & Kumar, S. A potential medicinal importance of zinc in human health and chronic. Int. J. Pharm. 1 , 05–11 (2010).

Mahmud, M. A. et al. Low temperature processed ZnO thin film as electron transport layer for efficient perovskite solar cells. Sol. Energy Mater. Sol. Cells. 159 , 251–264 (2017).

Rajan, S. & Ishak, N. S. Estimation of target hazard quotients and potential health risks for metals by consumption of shrimp ( Litopenaeus vannamei ) in Selangor, Malaysia. Sains Malays. 46 , 1825–1830 (2017).

Bamuwamye, M. et al. Human health risk assessment of heavy metals in Kampala (Uganda) drinking water. J. Food Res. 6 , 6–16 (2017).

Saleh, H. N. et al. Carcinogenic and non-carcinogenic risk assessment of heavy metals in groundwater wells in Neyshabur Plain, Iran. Biol. Trace Elem. Res. 190 , 251–261 (2019).

Tani, F. H. & Barrington, S. Zinc and copper uptake by plants under two transpiration rates Part II Buckwheat ( Fagopyrum esculentum L.). Environ. Pollut. 138 , 548–558 (2005).

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Acknowledgements

The authors wish to thank the University of Venda Health, Safety and Research Ethics’ Committee, the Department of Water affairs, Limpopo province and Vhembe district Municipality for granting the permission to conduct this study. We also thank all the respondents from the selected households in Lufule community.

The study was funded by the Research and Publication Committee of the University of Venda (Grant number: SHS/19/PH/14/1104).

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L.N. and J.N.E. conceptualized the study, L.N. collected and analysed the data, T.G.T., J.T. M., and J.N.E. supervised the data collection and analysis. F.C.O. drafted the original manuscript, J.N.E. reviewed and edited the original manuscript. All authors approved the final manuscript.

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Luvhimbi, N., Tshitangano, T.G., Mabunda, J.T. et al. Water quality assessment and evaluation of human health risk of drinking water from source to point of use at Thulamela municipality, Limpopo Province. Sci Rep 12 , 6059 (2022). https://doi.org/10.1038/s41598-022-10092-4

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