Ground water quality assessment using pattern recognition techniques: A case study on Khafr aquifer (Jahrom, Iran)

Subject Areas : Assessment and Management of Water, Soil, Air and Noise Pollution and Ecosystems Health

Homa Razmkhah ^{1 *}

1 -

Received: 2025-09-19 Published : 2025-10-26

Keywords: Groundwater quality, Cluster Analysis, Pattern Recognition Technique, Principal Component Analysis. ,

Abstract :

The knowledge of physicochemical characteristics has special significance in arid and semi-arid zones where ground water (GW) is the main source of water. The study of GW hydrochemistry of the Khafr aquifer in Jahrom (Fars, Iran) produced a large geochemical dataset. GW samples were collected at 18 sites, and analyzed for 12 variables. Principal Component Analysis (PCA) and Cluster Analysis (CA) were applied to the dataset to evaluate their usefulness to classify GW samples, and identify geochemical processes. Scree plot extracted two significant components explaining 93% of total variance. Component 1 with high and positive scores on Ca²⁺, K⁺, Cl^-, Na⁺, TDS, EC, SO₄^2-, and SAR, explains 55.5% of variance, pointing to a common origin for these minerals like dissolution of limestone, marl and gypsum in water. Component 2 containing 37.5% of variance, includes high and positive scores on TH, HCO₃^-, SO₄^2-, Ca²⁺ and Mg²⁺, and negative on pH. From their loadings, the components were defined as the salinity and hardness. PCA in combination with CA has nearly allowed identification and assessment of spatial sources of variation affecting hydrochemistry of GW. CA was not able to define details but guided through classification. Well 3 in the neighbourhood of salty braid of Ghareh Aghaj river was recognized as the most polluted one. The results will be helpful for the decision makers to adopt suitable remedial measures to protect GW sources.

 

References:

[1] M. Alavi. Regional stratigraphy of the Zagros fold-thrust belt of Iran and its proforeland evolution. American J. Science. 2004, 304, 1-20. https://doi.org/10.2475/ajs.304.1.1.
[2] E. M. Andrade, H. A. Q. Palacio, I. H. Souza, R. A. Oliveira Leao, M. J. Guerreiro. Land use effects in groundwater composition of an alluvial aquifer (Trussu River, Brazil) by multivariate techniques. Environmental Research. 2008, 106, 170-177. https://doi.org/10.1016/j.envres.2007.10.008.
[3] AOAC. Official Methods of Analysis. Vol. 1, 15th ed. Association of Analytical Chemists, Arlington, VI, U.S.A. 1990, p. 312. https://www.amazon.com/Official-Association-Analytical-Chemists-Fifteenth/dp/0935584420.
[4] APHA-AWWA-WEF. Standard Methods for the Examination of Water and Wastewater. 21st ed., American Public Health Association, American Water Works Association, Water Environment Federation, U.S.A. 2005. https://books.google.com/books/about/Standard_Methods_for_the_Examination_of.html?id=V2LhtAEACAAJ.
[5] J. Ashjari, and E. Raeisi. Lithological control on water chemistry in karst aquifers of the Zagros Range, Iran. Cave and Karst Science. 2006, 33(3), 111-118. https://bcra.org.uk/pub/candks/index.html?j=99.
[6] S. Battaleb-Looie, F. Moor, H. Jafari, G. Jacks, D. Ozsvath. Hyrdochemical evolution of groundwaters with excess fluoride concentrations from Dashtestan, south of Iran. Environmental Earth Science. 2012, 67, 1173-1182. https://doi.org/10.1007/s12665-012-1560-z.
[7] L. G. Closs, I. Nichol. The role of factor and regression analysis in the interpretation of geochemical reconnaissance data. Canadian J. Earth Science. 1975, 12, 1316-1330. https://doi.org/10.1139/e75-122.
[8] V. Cloutier, R. Lefebvre, R., Therrien, M. M. Savard. Multivariate statistical analysis of geochemical data as indicative of the hydrogeochemical evolution of groundwater in a sedimentary rock aquifer system. J. Hydrology. 2008. 353, 294-313. https://doi.org/10.1016/j.jhydrol.2008.02.015
[9] W. R. Dillon, M. Goldstein. Multivariate analysis methods and application. John and Wiley and Sons. 1984. https://www.wiley.com/en-us/Multivariate+Analysis%3A+Methods+and+Applications-p-9780471083177.
[10] Council Directive 80/778/EEC of the 15 July 1980 related to the quality of water intended for human consumption. http://data.europa.eu/eli/dir/1980/778/oj.
[11] N. L. Falcon. Problems of relationship between surface structure and deep displacement illustrated by Zagros Range, in time and place, in orogeny, SP. Pub. Geol. Soc. London. 1969. https://doi.org/10.1144/GSL.SP.1969.003.01.02.
[12] F. Fayazi, R. Lak, M. Nakhaei. Hydrogeochemistry and brine evolution of Maharlou salin lake, southern of Iran. Carbonates and Evaporites. 2007, 22(1), 33-42. https://doi.org/10.1007/BF03175844.
[13] C. Guler, M. A. Kurt, M. Alpaslan, C. Akbulut. Assessment of the impact of anthropogenic activities on the groundwater hydrology and chemistry in Tarsus coastal plain (Mersin, SE Turkey) using fuzzy clustering, multivariate statistics and GIS techniques. J. Hydrology. 2012, 414-415, 435-451. https://doi.org/10.1016/j.jhydrol.2011.11.021.
[14] T. Hill, P. Lewicki. Statistics Methods and Applications. Stat Soft Inc, Tulsa, OK.: Statistica, Version 8. 2007. https://doi.org/10.1007/s10182-007-0038-x.
[15] J. E. Jackson. A User's Guide to Principal Components. Wiley, New York. 1991. https://onlinelibrary.wiley.com/doi/book/10.1002/0471725331.
[16] R. A. Johnson, D. W. Wichern. Applied multivariate statistical analysis. Prentice-Hall International. 1992. https://link.springer.com/book/10.1007/978-3-662-45171-7.
[17] S. P. J. Kumar, P. Jegathambal, E. J. James. Multivariate and geostatistical analysis of groundwater quality in Palar river basin. International J. Geology. 2011, 4(5), 108-119. https://www.researchgate.net/publication/216216488_Multivariate_and_Geostatistical_Analysis_of_Groundwater_Quality_in_Palar_River_Basin.
[18] Ch.-W Liu, Ch.-Sh. Jang, Ch.-P. Chen, Ch.-N. Lin, K.-L. Lou. Characterization of groundwater quality in Kinmen island using multivariate analysis and geochemical modeling. Hydrological Processes. 2007, 22, 376-383. https://doi.org/10.1002/hyp.6606.
[19] D. L. Massart, L. Kaufman, 1983. The Interpretation of Analytical Chemical Data by the Use of Cluster Analysis. Wiley, New York. 1983. https://www.amazon.com/Interpretation-Analytical-Chemical-Cluster-Analysis/dp/0894643584.
[20] S. N. Deming, Michotte, Y., D. L. Massart, L. Kaufman, B.G. M. Vandeginste. Chemometrics: A Textbook. Elsevier, Amsterdam. 1988. https://www.amazon.com/Chemometrics-Textbook-S-N-Deming/dp/0444548319.
[21] R. R. Meglen. Examining large databases: a chemometric approach using principal component analysis. Marin Chemistry. 1992, 39, 217-237. http://dx.doi.org/10.1016/0304-4203(92)90103-H.
[22] M. Mellinger. Multivariate data analysis: its methods. Chemometerics and Intelligent Laboratory Systems. 1987, 2, 29-36. https://doi.org/10.1016/0169-7439(87)80083-7.
[23] S. Nejand, R. A. Khan. Ground-water quality in the Shiraz basin, south Iran. Ground Water. 1975, 13(3), 269-274. https://doi.org/10.1111/j.1745-6584.1975.tb03085.x
[24] H. Razmkhah, A. Abrishamchi, A., Torkian. Evaluation of spatial and temporal variation in water quality by pattern recognition techniques: A case study on Jajrood River (Tehra, Iran). J. Environmental Management. 2010, 91, 852-860. https://doi.org/10.1016/j.jenvman.2009.11.001.
[25] F. Sanchez-Martoz, R., Jimenez-Espinosa, A., Pulido-Bosch. Mapping ground water quality variables using PCA and geostatistics: a case study of Bajo Andarax, southeastern Spain. Hydrological Science J. 2010, 46(2), 227-242. https://doi.org/10.1080/02626660109492818.
[26] M. A. Sharaf, D. L. Illman, B. R. Kowalski. Chemometrics. Wiley, New York. 1986. https://doi.org/10.1002/jcc.540090712.
[27] K. P. Singh, A. Malik, D. Mohan, S. Sinha. Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River, (India)—a case study. Water Research. 2004, 38, 3980–3992. https://doi.org/10.1016/j.watres.2004.06.011.
[28] P. K. Srivastava, D. Han, M. Gupta, S. Mukherjee. Integrated framework for monitoring groundwater pollution using a geographical information system and multivariate analysis. Hydrological Science J. 2012, 57(7), 1453-1472. https://doi.org/10.1080/02626667.2012.716156.
[29] J. Stocklin. Structural history and tectonics of Iran; a review. AAPG Bulletin. 1968, 52(7): 1229-1258. https://doi.org/10.1306/5D25C4A5-16C1-11D7-8645000102C1865D.
[30] G. Tchobanoglous, E. D. Schroeder. Water quality: characteristics, modeling and modification. Addison-Wesley Publishing Company, Boston, MA. 1985. https://www.amazon.com/Water-Quality-Characteristics-Modeling-Modification/dp/0201054337.
[31] P. Willet. Similarity and Clustering in Chemical Information Systems. Research Studies Press, Wiley, New York. 1987. https://books.google.com/books/about/Similarity_and_Clustering_in_Chemical_In.html?id=yQvwAAAAMAAJ.
[32] D. A. Wunderlin, D. M. Pilar, A. M. Valeria, P. S. Fabiana, H. A. Cecilia, M. A. Bistoni. Pattern recognition techniques for the evaluation of spatial and temporal variations in water quality, A case study: Suquie a river basin (Cordoba-Argentina). Water Research. 2001, 35(12), 2881-2894. https://doi.org/10.1016/S0043-1354(00)00592-3.
[33] S. M. Yidana, B. Banoeng-Yakubo, Th. M. Akabzaa. Analysis of ground water quality using multivariate and spatial analysis in Keta basin, Ghana. J African Earth Science. 2010, 58(2), 220-234. https://doi.org/10.1016/j.jafrearsci.2010.03.003