Abstract
In this study, source water, finished water, and tap water were sampled monthly from two large drinking water treatment plants in Wuhan city, China for 12 months where physicochemical and microbiological parameters were measured, and the complex monitoring data was analyzed using single-factor assessment method, entropy weight water quality index (EWQI), and multivariate statistical techniques (i.e., cluster analysis (CA), discriminant analysis, and correlation analysis). The results of the single-factor assessment method showed that the total nitrogen pollution was the main problem in the source water quality, and the finished and tap water met the required quality standards. The EWQI values indicated that the overall quality of the source, finished, and tap water samples was “Excellent.” In addition, strengthening monitoring of parameters with high entropy weights, including Pb, Hg, sulfide, Cr in surface water and Hg, aerobic bateria count, and As in drinking water, were suggested, as they were prone to drastic changes. Spatial CA grouped the finished and tap water samples from the same plant into a cluster. Temporal CA grouped 12 sampling times of source water into Cluster 1 (June), Cluster 2 (April–May, and July–November), and Cluster 3 (December–March). Concerning finished and tap water, except the October was regrouped, the result of temporal CA was consistent to that of the source water. Based on similar characteristics of water samples, monitoring sites and frequency can be optimized. Moreover, stepwise discriminant analysis indicated that the spatiotemporal variations in water quality among CA-groups were enough to be explained by four or five parameters, which provided a basis for the selection of monitoring parameters. The results of correlation analysis showed that few pairwise correlations were both significant (P < 0.05) and stable across sampling sites, suggesting that the number of monitoring parameters was difficult to reduce through substitution. In summary, this study illustrates the usefulness of EWQI and the multivariate statistical techniques in the water quality assessment and monitoring strategy optimization.
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References
Abokifa AA, Yang YJ, Lo CS, Biswas P (2016) Investigating the role of biofilms in trihalomethane formation in water distribution systems with a multicomponent model. Water Res 104:208–219
Amiri V, Rezaei M, Sohrabi N (2014) Groundwater quality assessment using entropy weighted water quality index (EWQI) in Lenjanat, Iran. Environ Earth Sci 72:3479–3490
Bhuiyan MAH, Bodrud-Doza M, Islam A, Rakib MA, Rahman MS, Ramanathan AL (2016) Assessment of groundwater quality of Lakshimpur district of Bangladesh using water quality indices, geostatistical methods, and multivariate analysis. Environ Earth Sci 75
Bond T, Huang J, Templeton MR, Graham N (2011) Occurrence and control of nitrogenous disinfection by-products in drinking water--a review. Water Res 45:4341–4354
Chai YX, Xiao CL, Li MQ, Liang XJ (2020) Hydrogeochemical characteristics and groundwater quality evaluation based on multivariate statistical analysis. Water 12
Chaves RS, Guerreiro CS, Cardoso VV, Benoliel MJ, Santos MM (2019) Hazard and mode of action of disinfection by-products (DBPs) in water for human consumption: Evidences and research priorities. Comp Biochem Physiol C Toxicol Pharmacol 223:53–61
Chen T, Zhang HF, Sun CX, Li HY, Gao Y (2018) Multivariate statistical approaches to identify the major factors governing groundwater quality. Appl Water Sci 8:215
Ding SF, Shi ZZ (2005) Studies on incidence pattern recognition based on information entropy. J Inf Sci 31:497–502
Etheridge JR, Randolph M, Humphrey C (2019) Real-time estimates of Escherichia coli concentrations using ultraviolet-visible spectrometers. J Environ Qual 48:531–536
Fang Y, Zheng T, Zheng X, Peng H, Wang H, Xin J, Zhang B (2020) Assessment of the hydrodynamics role for groundwater quality using an integration of GIS, water quality index and multivariate statistical techniques. J Environ Manage 273:111185
Gong Y, Huang Y, Wang M, Liu F, Zhang T (2019) Application of iron-based materials for remediation of mercury in water and soil. Bull Environ Contam Toxicol 102:721–729
Gulgundi MS, Shetty A (2018) Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques. Appl Water Sci 8
Haas C (2011) Water quality & treatment. American Water Works Association, Colorado, United States
Han D, Currell MJ (2017) Persistent organic pollutants in China’s surface water systems. Sci Total Environ 580:602–625
Han X, Liu XH, Gao DT, Ma BJ, Gao XY, Cheng MK (2022) Costs and benefits of the development methods of drinking water quality index: a systematic review. Ecol Indic 144:109501
Kadwa U, Kumarasamy MV, Stretch D (2018) Effect of chlorine and chloramine disinfection and the presence of phosphorous and nitrogen on biofilm growth in dead zones on PVC pipes in drinking water systems. J S Afr Inst Civ Eng 60:45–50
Khalil B, Ouarda T, St-Hilaire A, Chebana F (2010) A statistical approach for the rationalization of water quality indicators in surface water quality monitoring networks. J Hydrol 386:173–185
Khanoranga KS (2019) An assessment of groundwater quality for irrigation and drinking purposes around brick kilns in three districts of Balochistan province, Pakistan, through water quality index and multivariate statistical approaches. J Geochem Explor 197:14–26
Kildare BJ, Leutenegger CM, McSwain BS, Bambic DG, Rajal VB, Wuertz S (2007) 16S rRNA-based assays for quantitative detection of universal, human-, cow-, and dog-specific fecal Bacteroidales: a Bayesian approach. Water Res 41:3701–3715
Kim H, Jang G, Yoon Y (2020) Specific heavy metal/metalloid sensors: current state and perspectives. Appl Microbiol Biotechnol 104:907–914
Leight AK, Crump BC, Hood RR (2018) Assessment of fecal indicator bacteria and potential pathogen co-occurrence at a shellfish growing area. Front Microbiol 9:384
Li PY, Qian H, Wu JH (2010) Groundwater quality assessment based on improved water quality index in Pengyang County, Ningxia, Northwest China. E-J Chem 7:S209–S216
Lupo A, Coyne S, Berendonk TU (2012) Origin and evolution of antibiotic resistance: the common mechanisms of emergence and spread in water bodies. Front Microbiol 3
Matiatos I, Alexopoulos A, Godelitsas A (2014) Multivariate statistical analysis of the hydrogeochemical and isotopic composition of the groundwater resources in northeastern Peloponnesus (Greece). Sci Total Environ 476-477:577–590
Mester T, Balla D, Szabo G (2020) Assessment of groundwater quality changes in the rural environment of the hungarian great plain based on selected water quality indicators. Water Air Soil Pollut 231:536
Ministry of Enviromental Protection of the People’s Republic of China (2002) Environmental quality standards for surface water
Ministry of Environmental Protection (2009) Water quality—guidance on sampling techniques
Ministry of Health of the People's Republic of China (2006) Standards for drinking water quality
Ministry of Health of the People’s Republic of China (2006) Standard examination methods for drinking water
Ministry of Water Resources of the People’s Republic of China (2013) Regulation for water environmental monitoring
Nakar A, Schmilovitch Z, Vaizel-Ohayon D, Kroupitski Y, Borisover M, Sela S (2020) Quantification of bacteria in water using PLS analysis of emission spectra of fluorescence and excitation-emission matrices. Water Res 169:115197
New Jersey Department of Health (2015) Hazardous substance fact sheet-chlorine
Nong XZ, Yi XJ, Chen LH, Shao DG, Zhang C (2023) Impact of inter-basin water diversion project operation on water quality variations of Hanjiang River, China. Front Ecol Evol:11
Nosrati K, Van Den Eeckhaut M (2012) Assessment of groundwater quality using multivariate statistical techniques in Hashtgerd Plain, Iran. Environ Earth Sci 65:331–344
Papaioannou A, Dovriki E, Rigas N, Plageras P, Rigas I, Kokkora M, Papastergiou P (2010) Assessment and modelling of groundwater quality data by environmetric methods in the context of public health. Water Resour Manage 24:3257–3278
Petalas C, Anagnostopoulos K (2006) Application of stepwise discriminant analysis for the identification of salinity sources of groundwater. Water Resour Manage 20:681–700
Shannon C (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423
Singh EJ, Gupta A, Singh NR (2013) Groundwater quality in Imphal West district, Manipur, India, with multivariate statistical analysis of data. Environ Sci Pollut Res Int 20:2421–2434
Smeti EM, Thanasoulias NC, Lytras ES, Tzoumerkas PC, Golfinopoulos SK (2009) Treated water quality assurance and description of distribution networks by multivariate chemometrics. Water Res 43:4676–4684
Soltani S, Asghari Moghaddam A, Barzegar R, Kazemian N, Tziritis E (2017) Hydrogeochemistry and water quality of the Kordkandi-Duzduzan plain, NW Iran: application of multivariate statistical analysis and PoS index. Environ Monit Assess 189:455
Srivastav AL, Patel N, Chaudhary VK (2020) Disinfection by-products in drinking water: occurrence, toxicity and abatement. Environ Pollut 267:115474
Sutadian AD, Muttil N, Yilmaz AG, Perera BJ (2016) Development of river water quality indices-a review. Environ Monit Assess 188:58
Urban-Chmiel R, Marek A, Stępień-Pyśniak D, Wieczorek K, Dec M, Nowaczek A, Osek J (2022) Antibiotic resistance in bacteria-a review. Antibiotics (Basel) 11
Wagner ED, Plewa MJ (2017) CHO cell cytotoxicity and genotoxicity analyses of disinfection by-products: an updated review. J Environ Sci (China) 58:64–76
Wali SU, Alias NB, Bin Harun S, Umar KJ, Gada MA, Dankani IM, Kaoje IU, Usman AA (2022) Water quality indices and multivariate statistical analysis of urban groundwater in semi-arid Sokoto Basin, Northwestern Nigeria. Groundw Sustain Dev 18:100779
Wang H, Hu C, Shi B (2021) The control of red water occurrence and opportunistic pathogens risks in drinking water distribution systems: a review. J Environ Sci (China) 110:92–98
Wang J, Deng ZQ (2019) Modeling and predicting fecal coliform bacteria levels in oyster harvest waters along Louisiana Gulf coast. Ecol Indic 101:212–220
Wang P, Hu J, Liu T, Liu J, Ma S, Ma W, Li J, Zheng H, Lu R (2023) Advances in the application of metallic isotopes to the identification of contaminant sources in environmental geochemistry. J Hazard Mater 458:131913
Ward MH, Jones RR, Brender JD, De Kok TM, Weyer PJ, Nolan BT, Villanueva CM, Van Breda SG (2018) Drinking water nitrate and human health: an updated review. Int J Environ Res Public Health 15:1557
WHO (2011) Guidelines for drinking-water quality. WHO Press, Geneva, Switzerland
Wu J, Li P, Qian H (2011) Groundwater quality in Jingyuan County, a semi-humid area in Northwest China. J Chem 8:787–793
Wu J (2020) Challenges for safe and healthy drinking water in China. Curr Environ Health Rep 7:292–302
Xia K, Hou HB, Wang SX, Lv Y, Zhou ZH, Zhou M (2014) The environment risk analysis and prevention countermeasures of potable water sources in wuhan section of Yangtze River. Adv Mat Res 864-867:844–848
Xiong Y (2016) Simulation study of the effect of effluent of Chenjiashan gate on source water quality of Baishizhou waterworks. Dissertation. Huazhong University of Science and Technology
Yang LX, Zhang YY, Wang FF, Luo ZDE, Guo SJ, Strahle U (2020) Toxicity of mercury: molecular evidence. Chemosphere 245
Yu C et al (2019) Managing nitrogen to restore water quality in China. Nature 567:516–520
Zhang JH, Guo LQ, Huang T, Zhang DD, Deng ZM, Liu LS, Yan T (2022) Hydro-environmental response to the inter-basin water resource development in the middle and lower Han River, China. Hydrol Res 53:141–155
Zhang X, Zhang Y, Shi P, Bi Z, Shan Z, Ren L (2021) The deep challenge of nitrate pollution in river water of China. Sci Total Environ 770:144674
Zhang YY, Ban X, Li EH, Wang Z, Xiao F (2020) Evaluating ecological health in the middle-lower reaches of the Hanjiang River with cascade reservoirs using the Planktonic index of biotic integrity (P-IBI). Ecol Indic 114
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The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
Funding
This work was supported by the Fundamental Research Funds for the Central Universities in China (No. 2015TS103), the Cooperative Agreement from the Wuhan Center for Disease Control and Prevention (No. 20212303), and the Doctoral Scientific Research Fund of Henan University of Chinese Medicine (No. RSBSJJ2020-09).
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Conceptualization: XH, FT, and A-LL; methodology: XH, FT, and A-LL; formal analysis and investigation: XH; writing—original draft preparation: XH; writing—review and editing: XH, FT, and A-LL; funding acquisition: XH and A-LL; resources: FT and A-LL; supervision: FT and A-LL.
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Highlights
•Multiple methods were used to assess the water quality of two large-scale waterworks.
•The total nitrogen is the main problem in the source water quality.
•The overall quality of surface water and drinking water was “Excellent.”
•EWQI, CA, and DA can complement preexisting methods and add new insights.
•Cluster and discriminant analyses help in improving the monitoring efficiency.
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Han, X., Tang, F. & Liu, AL. Drinking water quality evaluation in supply systems in Wuhan, China: application of entropy weight water quality index and multivariate statistical analysis. Environ Sci Pollut Res 31, 280–292 (2024). https://doi.org/10.1007/s11356-023-31212-1
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DOI: https://doi.org/10.1007/s11356-023-31212-1