*Result*: A novel framework for groundwater quality evaluation in industrial zone using unsupervised machine learning methods.
Title:
A novel framework for groundwater quality evaluation in industrial zone using unsupervised machine learning methods.
Authors:
Panneerselvam M; Department of Civil Engineering, M.Kumarasamy College of Engineering, Karur, 639113, India. mukeshssoft@gmail.com., Govindan V; Department of Civil Engineering, University College of Engineering- BIT Campus, Anna University, Tiruchirappalli, 620024, India., Sakthivel LP; Department of Pharmaceutical Technology, University College of Engineering- BIT Campus, Anna University, Tiruchirappalli, 620024, India. slaxmanvel@aubit.edu.in.
Source:
Environmental geochemistry and health [Environ Geochem Health] 2026 Feb 14; Vol. 48 (4), pp. 161. Date of Electronic Publication: 2026 Feb 14.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Kluwer Academic Publishers Country of Publication: Netherlands NLM ID: 8903118 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-2983 (Electronic) Linking ISSN: 02694042 NLM ISO Abbreviation: Environ Geochem Health Subsets: MEDLINE
Imprint Name(s):
Publication: 1999- : Dordrecht : Kluwer Academic Publishers
Original Publication: Kew, Surrey : Science and Technology Letters, 1985-
Original Publication: Kew, Surrey : Science and Technology Letters, 1985-
MeSH Terms:
References:
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Ahamad, M. I., Rehman, A., Mehmood, M. S., Mahmood, S., Zafar, Z., Lu, H., & Lu, S. (2024). Spatial distribution, ecological and human health risks of potentially toxic elements (PTEs) in river Ravi, Pakistan: A comprehensive study. Environmental Research, 263, Article 120205. (PMID: 10.1016/j.envres.2024.120205)
Ahamed, A. J., Loganathan, K., & Jayakumar, R. (2015). Hydrochemical characteristics and quality assessment of groundwater in Amaravathi river basin of Karur district, Tamil Nadu, South India. Sustainable Water Resources Management, 1(3), 273–291. (PMID: 10.1007/s40899-015-0026-3)
Ahmad, S., Umar, R., & Ahmad, I. (2024). Assessment of groundwater quality using Entropy-Weighted Quality INDEX (EWQI) and multivariate statistical techniques in Central Ganga plain, India. Environment, Development and Sustainability, 26(1), 1615–1643. (PMID: 10.1007/s10668-022-02776-8)
Alam, K., Nafees, M., Ali, W., Muhammad, S., & Raziq, A. (2025). Geogenic contamination of groundwater in a highland watershed: hydrogeochemical assessment, source apportionment, and health risk evaluation of fluoride and nitrate. Hydrology, 12(4), Article 70. (PMID: 10.3390/hydrology12040070)
APHA. (1999). Standard methods for the examination of water and wastewater, 20th edn. American Public Health Association, Washington DC.
Benaafi, M., Abba, S. I., & Aljundi, I. H. (2023b). Effects of seawater intrusion on the groundwater quality of multi-layered aquifers in eastern Saudi Arabia. Molecules, 28(7), Article 3173. (PMID: 10.3390/molecules28073173)
Benaafi, M., Abba, S. I., Tawabini, B., Abdulazeez, I., Salhi, B., Usman, J., & Aljundi, I. H. (2023a). Integrated clustering analysis for delineating seawater intrusion and heavy metals in Arabian Gulf Coastal groundwater of Saudi Arabia. Heliyon. https://doi.org/10.1016/j.heliyon.2023.e19784. (PMID: 10.1016/j.heliyon.2023.e19784)
Central Ground Water Board (CGWB), 2021, Groundwater pollution, Press Information Bureau, India. ( https://pib.gov.in/Pressreleaseshare.aspx?PRID=1777262 ) Accessed on 27–02–2025.
De, A., Ghosh, S., Dey, A., Islam, K. H., Maji, K., Mandal, J., & Roychowdhury, T. (2024). Assessing groundwater fluoride contamination scenario in West Bengal, India: A combined approach using meta-analysis, current research, and health risk evaluation. Groundwater for Sustainable Development. https://doi.org/10.1016/j.gsd.2024.101286. (PMID: 10.1016/j.gsd.2024.101286)
Eid, M. H., Eissa, M., Mohamed, E. A., Ramadan, H. S., Czuppon, G., Kovács, A., & Szűcs, P. (2024). Application of stable isotopes, mixing models, and K-means cluster analysis to detect recharge and salinity origins in Siwa Oasis, Egypt. Groundwater for Sustainable Development, 25, Article 101124. (PMID: 10.1016/j.gsd.2024.101124)
El Mountassir, O., Bahir, M., Ouazar, D., Chehbouni, A., & Carreira, P. M. (2022). Temporal and spatial assessment of groundwater contamination with nitrate using nitrate pollution index (NPI), groundwater pollution index (GPI), and GIS (case study: Essaouira basin, Morocco). Environmental Science and Pollution Research, 29(12), 17132–17149. (PMID: 10.1007/s11356-021-16922-8)
Festa, D., Novellino, A., Hussain, E., Bateson, L., Casagli, N., Confuorto, P., & Raspini, F. (2023). Unsupervised detection of InSAR time series patterns based on PCA and K-means clustering. International Journal of Applied Earth Observation and Geoinformation, 118, Article 103276. (PMID: 10.1016/j.jag.2023.103276)
Gao, M., Qian, J., Li, X., Wang, Z., Hou, X., Gui, C., Bai, Z., Li, J., Zuo, X., & Zhao, C. (2024). Assessment of groundwater quality using Entropy-Weighted Quality Index (EWQI) and multivariate statistical approaches in Heilongdong Spring Basin, Northern China. Environmental Earth Sciences, 83(7), Article 196. (PMID: 10.1007/s12665-024-11458-9)
Golla, V. S., & Badapalli, P. K. (2022). Evaluation of water quality for drinking and irrigation purposes and Fluoride Health Hazard Risk Assessment (HHRA) in parts of semi-arid regions in the south-eastern part of India. International Journal of Energy and Water Resources, 6(4), 521–529. (PMID: 10.1007/s42108-021-00145-1)
Haji, M., Karuppannan, S., Qin, D., Shube, H., & Kawo, N. S. (2021). Potential human health risks due to groundwater fluoride contamination: A case study using multi-techniques approaches (GWQI, FPI, GIS, HHRA) in Bilate River Basin of Southern main Ethiopian Rift, Ethiopia. Archives of Environmental Contamination and Toxicology, 80(1), 277–293. (PMID: 10.1007/s00244-020-00802-2)
Kada, H., Demdoum, A., & Aouati, H. (2023). Groundwater contamination apportionment in Beida-Bordj rural territory, northeast Algeria, using the nitrate pollution index (NPI) and groundwater pollution index (GPI). Sustainable Water Resources Management, 9(5), Article 152. (PMID: 10.1007/s40899-023-00931-1)
Karunanidhi, D., Aravinthasamy, P., Roy, P., Subramani, T., & Jayasena, H. C. (2024). Nitrate contamination in groundwater and its evaluation of non-carcinogenic health hazards from Arjunanadi River basin, south India. Groundwater for Sustainable Development, 25, Article 101153. (PMID: 10.1016/j.gsd.2024.101153)
Karuppannan, S., Panneerselvam, B., Haji, M., Murugesan, B., Shube, H., & SerreKawo, N. (2022). Evaluation of groundwater quality and its suitability for drinking and cultivation practices in and around around the deltaic regions of South India using DWQI, IWQI, and GIS. Climate Change Impact on Groundwater Resources: Human Health Risk Assessment in Arid and Semi-arid Regions (pp. 181–200). Springer International Publishing. (PMID: 10.1007/978-3-031-04707-7_10)
Kom, K. P., Gurugnanam, B., Bairavi, S., & Chidambaram, S. (2023). Sources and geochemistry of high fluoride groundwater in hard rock aquifer of the semi-arid region. a special focus on human health risk assessment. Total Environment Research Themes, 5, Article 100026. (PMID: 10.1016/j.totert.2023.100026)
Kumari, M., Singh, S., & Kumar, A. (2024). Groundwater prospect zone mapping: A geospatial investigation with decision making in Mahendergarh District, Haryana. Asian Journal of Water, Environment and Pollution, 21(6), 131–141. (PMID: 10.3233/AJW240080)
Lanjwani, M. F., Khuhawar, M. Y., Khuhawar, T. M. J., Memon, S. Q., Samtio, M. S., Lanjwani, A. H., & Rind, I. K. (2022). Spatial distribution of hydrochemistry and characterization of groundwater of taluka Bakrani, Larkana, Sindh, Pakistan. Arabian Journal of Geosciences, 15(5), Article 380. (PMID: 10.1007/s12517-022-09609-y)
Latha, P. S. (2022). Evaluation of groundwater quality for domestic and irrigation purposes in a coastal alluvial aquifer using multivariate statistics and entropy water quality index approach: A case study from West Godavari Delta, Andhra Pradesh (India). Environmental Earth Sciences, 81(10), Article 275. (PMID: 10.1007/s12665-022-10387-9)
Mao, H., Wang, G., Rao, Z., Liao, F., Shi, Z., Huang, X., & Yang, Y. (2021). Deciphering spatial pattern of groundwater chemistry and nitrogen pollution in Poyang Lake Basin (eastern China) using self-organizing map and multivariate statistics. Journal of Cleaner Production, 329, Article 129697. (PMID: 10.1016/j.jclepro.2021.129697)
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Contributed Indexing:
Keywords: Entropy water quality index; Groundwater chemistry; Groundwater pollution index; Human health risk; Unsupervised machine learning methods
Substance Nomenclature:
0 (Water Pollutants, Chemical)
Entry Date(s):
Date Created: 20260214 Date Completed: 20260214 Latest Revision: 20260311
Update Code:
20260311
DOI:
10.1007/s10653-026-03052-8
PMID:
41689606
Database:
MEDLINE
*Further Information*
*Population density, urbanization and industrialization are the rapidly increasing and it's causes severe damages to freshwater ecosystem. The present study aims to assess the quality of groundwater using integrated methods in the industrial zone of South India. The integrated assessment of groundwater using unsupervised machine learning method associated human health risk assessment are identified as research gap in the study region. We collected 55 samples based on groundwater availability, population density, and industrial activity in summer and winter seasons. The study found that calcium-chloride and mixed calcium-magnesium-chloride types of water are the dominating category in both seasons. The groundwater pollution index (GPI) and piper trilinear and gibbs diagram indicate that evaporation, water-rock interface, and other anthropogenic activities are the dominating factors in groundwater chemistry. Analysis using the entropy water quality index (EWQI) and human health risk estimation confirmed that nitrate is the key parameter affecting groundwater sustainability. Unsupervised machine learning techniques were applied to evaluate groundwater chemistry. The principal component analysis (PCA) results revealed that seasonal variation is influenced by mineral dissolution, rainwater recharge, and anthropogenic activities. The hierarchical cluster analysis (HCA) results shows that a tight cluster forms among pH, Na, K, NO3, and F, suggesting that processes such as agricultural inputs from fertilizer use, synthetic pesticides, and natural geochemical interactions control ion exchange. The k-means clustering yielded three clusters: low-salinity fresh water, moderately mineralized water undergoing geochemical alteration, and high-hardness water indicative of specific geogenic and anthropogenic influences in both seasons. Overall, the integrated assessment of groundwater revealed that the water-rock interface, evaporation, and synthetic fertilizer use in agricultural fields are significant factors controlling groundwater quality. The key findings of this study provides clear knowledge about the nature of groundwater, influencing factors and help to improve the water resources management strategies in investigation zone.
(© 2026. The Author(s), under exclusive licence to Springer Nature B.V.)*