Skip to main content

Advertisement

SpringerLink
Log in

MLR index–based principal component analysis to investigate and monitor probable sources of groundwater pollution and quality in coastal areas: a case study in East India

  • Research
  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Identifying groundwater contamination sources and supervising groundwater quality conditions are urgently needed to protect the groundwater resources of coastal areas like Contai of India, as communities here are heavily relying on groundwater which deteriorates progressively. So current research aims to address in detail about origins and influencing factors of groundwater contamination, status, and monitoring water quality by employing extremely useful leading technologies like principal component and factor analyses (PCA/FA), groundwater quality index (GWQI), and multiple linear regression (MLR) that helps to simplify complicated works instead of the conventional methods. Eight groundwater quality parameters were evaluated here, such as pH, TH (total hardness), Tur (turbidity), EC (electrical conductivity), TDS (total dissolved solids), Mn (manganese), Fe (iron), and Cl (chloride) for 38 sites. Three principal components with ~ 81% of the total variance were extracted from the PCA/FA analysis. The origin of maximum loadings of each factor is identified as a result of saline water, disintegration and leaching process, organic or else biogenic activities, and lithogenic or otherwise non-lithogenic links through percolating water. GWQI results show that ~ 87% of the samples fall into the good category and ~ 13% of the samples fall into the poor to very poor category. A model consisting of Tur, Fe, EC, Mn, TH, and Cl as independent parameters is more feasible and is proposed to predict GWQI obtained from MLR analysis. This MLR model also suggests that turbidity with the highest beta coefficient (0.820) is a key contributor relative to the entire groundwater class in this affected area. The findings relating to this research may support the designer and officials in monitoring and protecting coastal groundwater resources like selected areas.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

All data analyzed during this study are included in this article.

References

  • Abulibdeh, A., Al-Awadhi, T., Nasiri, N. A., Al-Buloshi, A., & Abdelghani, M. (2021). Spatiotemporal mapping of groundwater salinity in Al-Batinah, Oman. Groundwater for Sustainable Development, 12, 100551. https://doi.org/10.1016/j.gsd.2021.100551

  • Akshitha, V., Balakrishna, K., & Udayashankar, H. N. (2021). Assessment of hydrogeochemical characteristics and saltwater intrusion in selected coastal aquifers of southwestern India. Marine Pollution Bulletin, 173, 112989. https://doi.org/10.1016/j.marpolbul.2021.112989

  • Alam, A., & Singh, A. (2023). Groundwater quality assessment using SPSS based on multivariate statistics and water quality index of Gaya, Bihar (India). Environmental Monitoring and Assessment, 195, 687. https://doi.org/10.1007/s10661-023-11294-7

    Article  CAS  Google Scholar 

  • Aminiyan, M. M., Aitkenhead-Peterson, J., & Aminiya, F. M. (2018). Evaluation of multiple water quality indices for drinking and irrigation purposes for the Karoon river. Iran. Environmental Geochemistry and Health, 40, 2707–2728. https://doi.org/10.1007/s10653-018-0135-7

    Article  CAS  Google Scholar 

  • APHA. (2017). Standard methods for the examination of water and wastewater (23rd ed.). Washington.

    Google Scholar 

  • Arslan, H. (2013). Application of multivariate statistical techniques in the assessment of groundwater quality in seawater intrusion area in Bafra Plain, Turkey. Environmental Monitoring and Assessment, 185, 2439–2452. https://doi.org/10.1007/s10661-012-2722-x

    Article  CAS  Google Scholar 

  • Arslan, H., & Demir, Y. (2013). Impacts of seawater intrusion on soil salinity and alkalinity in Bafra Plain, Turkey. Environmental Monitoring and Assessment, 185, 1027–1040. https://doi.org/10.1007/s10661-012-2611-3

    Article  CAS  Google Scholar 

  • Asare, A., Appiah-Adjei, E. K., Ali, B., & Owusu-Nimo, F. (2021). Physico-chemical evaluation of groundwater along the coast of the Central Region, Ghana. Groundwater for Sustainable Development, 13, 100571. https://doi.org/10.1016/j.gsd.2021.100571

  • Awachat, A. R., & Salkar, V. D. (2017). Ground water quality assessment through WQIs. International Journal of Engineering Research and Technology, 10, 318–322.

    Google Scholar 

  • Banda, D. T., & Kumarasamy, M. (2020). Application of multivariate statistical analysis in the development of a surrogate water quality index (WQI) for South African watersheds. Water, 12, 1584. https://doi.org/10.3390/w12061584

    Article  CAS  Google Scholar 

  • Boateng, T. K. B., Opoku, F., Acquaah, S. O., & Akoto, O. (2016). Groundwater quality assessment using statistical approach and water quality index in Ejisu-Juaben Municipality. Ghana. Environmental Earth Sciences, 75, 489. https://doi.org/10.1007/s12665-015-5105-0

    Article  CAS  Google Scholar 

  • Bodrud-Doza, M., Islam, A. R. M. T., Ahmed, F., Das, S., Saha, N., & Rahman, M. S. (2016). Characterization of groundwater quality using water evaluation indices, multivariate statistics and geostatistics in central Bangladesh. Water Science, 30(1), 19–40. https://doi.org/10.1016/j.wsj.2016.05.001

    Article  Google Scholar 

  • 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

    Article  CAS  Google Scholar 

  • Chakraborty, S., John, B., Maity, P. K., & Das, S. (2020). Increasing threat on groundwater reserves due to seawater intrusion in Contai belt of West Bengal. Journal of the Indian Chemical Society, 97(5), 799–817.

    CAS  Google Scholar 

  • Chen, T., Zhang, H., Sun, C., Li, H., & Gao, Y. (2018). Multivariate statistical approaches to identify the major factors governing groundwater quality. Applied Water Science, 8, 215. https://doi.org/10.1007/s13201-018-0837-0

    Article  CAS  Google Scholar 

  • Das, C. R., Das, S., & Panda, S. (2022). Groundwater quality monitoring by correlation, regression and hierarchical clustering analyses using WQI and PAST tools. Groundwater for Sustainable Development, 16, 100708. https://doi.org/10.1016/j.gsd.2021.100708

  • Dutta, S., Dwivedi, A., & Kumar, M. S. (2018). Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river. Environmental Monitoring and Assessment, 190, 718. https://doi.org/10.1007/s10661-018-7100-x

    Article  CAS  Google Scholar 

  • Ferchichi, H., Hamouda, M. F. B., Farhat, B., & Mammou, A. B. (2018). Assessment of groundwater salinity using GIS and multivariate statistics in a coastal Mediterranean aquifer. International Journal of Environmental Science and Technology, 15, 2473–2492. https://doi.org/10.1007/s13762-018-1767-y

    Article  CAS  Google Scholar 

  • Gholami, V., Khaleghi, R. M., & Sebghati, M. (2016). A method of groundwater quality assessment based on fuzzy network-CANFIS and geographic information system (GIS). Applied Water Science, 7(7), 3633–3647. https://doi.org/10.1007/s13201-016-0508-y

    Article  Google Scholar 

  • Gibrilla, A., Bam, E. K. P., Adomako, D., Ganyaglo, S., Osae, S., Akiti, T. T., Kebede, S., Achoribo, E., Ahialey, E., Ayanu, G., & Agyeman, E. K. (2011). Application of water quality index (WQI) and multivariate analysis for groundwater quality assessment of the Birimian and Cape Coast granitoid complex: Densu River Basin of Ghana. Water Quality, Exposure and Health, 3, 63. https://doi.org/10.1007/s12403-011-0044-9

    Article  CAS  Google Scholar 

  • Gradilla-Hernández, M. S., de Anda, J., Garcia-Gonzalez, A., Meza-Rodríguez, D., Montes, C. Y., & Perfecto-Avalos, Y. (2020). Multivariate water quality analysis of Lake Cajititlán. Mexico. Environmental Monitoring and Assessment, 192, 5. https://doi.org/10.1007/s10661-019-7972-4

    Article  CAS  Google Scholar 

  • Gulgundi, M. S., & Shetty, A. (2018). Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques. Applied Water Science, 8, 43. https://doi.org/10.1007/s13201-018-0684-z

    Article  CAS  Google Scholar 

  • Haghnazar, H., Johannesson, K. H., González-Pinzón, R, Pourakbar, M., Aghayani, E., Rajabi, A., & Hashemi, A. A. (2022). Groundwater geochemistry, quality, and pollution of the largest lake basin in the Middle East: Comparison of PMF and PCA-MLR receptor models and application of the source-oriented HHRA approach. Chemosphere, 288, 132489. https://doi.org/10.1016/j.chemosphere.2021.132489

  • Halder, S., Dhal, L., & Jha, M. K. (2021). Investigating groundwater condition and seawater intrusion status in coastal aquifer systems of eastern India. Water, 13, 1952. https://doi.org/10.3390/w13141952

    Article  CAS  Google Scholar 

  • Heydarirad, L., Mosaferi, M., Pourakbar, M., Esmailzadeh, N., & Maleki, S. (2019). Groundwater salinity and quality assessment using multivariate statistical and hydrogeochemical analysis along the Urmia Lakecoastal in Azarshahr Plain, North West of Iran. Environmental Earth Sciences, 78, 670. https://doi.org/10.1007/s12665-019-8655-8

    Article  CAS  Google Scholar 

  • IS 10500. (2012). Indian standard drinking water specification. Second Revision, Bureau of Indian Standards, New Delhi.

  • Islam, A. R. M. T., Shen, S., Haque, M. A., Bodrud-Doza, M., Maw, W. K., & Habib, M. A. (2018). Assessing groundwater quality and its sustainability in Joypurhat district of Bangladesh using GIS and multivariate statistical approaches. Environment, Development and Sustainability, 20, 1935–1959. https://doi.org/10.1007/s10668-017-9971-3

    Article  Google Scholar 

  • Jayathunga, K., Diyabalanage, S., Frank, A. H., Chandrajith, R., & Barth, J. A. C. (2020). Influences of seawater intrusion and anthropogenic activities on shallow coastal aquifers in Sri Lanka: Evidence from hydrogeochemical and stable isotope data. Environmental Science and Pollution Research, 27, 23002–23014. https://doi.org/10.1007/s11356-020-08759-4

    Article  CAS  Google Scholar 

  • Liu, C., Lin, K., & Kuo, Y. (2003). Application of factor analysis in the assessment of groundwater quality in a blackfoot disease area in Taiwan. Science of the Total Environment, 313(1–3), 77–89. https://doi.org/10.1016/S0048-9697(02)00683-6

    Article  CAS  Google Scholar 

  • Li, Q., Zhang, H., Guo, S., Fu, K., Liao, L., Xu, Y., & Cheng, S. (2019). Groundwater pollution source apportionment using principal component analysis in a multiple land-use area in southwestern China. Environmental Science and Pollution Research, 27, 9000–9011. https://doi.org/10.1007/s11356-019-06126-6

    Article  CAS  Google Scholar 

  • Li, W., Wu, J., Zhou, C., & Nsabimana, A. (2021). Groundwater pollution source identification and apportionment using PMF and PCA-APCS-MLR receptor models in Tongchuan City, China. Archives of Environmental Contamination and Toxicology, 81, 397–413. https://doi.org/10.1007/s00244-021-00877-5

    Article  CAS  Google Scholar 

  • Mahapatra, S. S., Sahu, M., Patel, R. K., & Panda, B. N. (2012). Prediction of water quality using principal component analysis. Water Quality, Exposure and Health, 4, 93–104. https://doi.org/10.1007/s12403-012-0068-9

    Article  CAS  Google Scholar 

  • Maity, P. K., Das, S., & Das, R. (2017). Assessment of groundwater quality and saline water intrusion in the coastal aquifers of Purba Midnapur district. Indian Journal of Environmental Protection, 37(1), 31–40.

    CAS  Google Scholar 

  • Maity, P. K., Das, S., & Das, R. (2018). A geochemical investigation and control management of saline water intrusion in the coastal aquifer of Purba Midnapur district in West Bengal, India. Journal of the Indian Chemical Society, 95, 205–210.

    Google Scholar 

  • Mondal, N. C., Singh, V. P., Singh, V., & S. & Saxena, V. K. (2010). Determining the interaction between groundwater and saline water through groundwater major ions chemistry. Journal of Hydrology, 388, 100–111. https://doi.org/10.1016/j.jhydrol.2010.04.032

    Article  CAS  Google Scholar 

  • Motevalli, A., Moradi, R. H., & Javadi, S. (2017). A comprehensive evaluation of groundwater vulnerability to saltwater up-coning and sea water intrusion in a coastal aquifer (case study: Ghaemshahr-juybar aquifer). Journal of Hydrology, 557, 753–773. https://doi.org/10.1016/j.jhydrol.2017.12.047

    Article  CAS  Google Scholar 

  • Mu, D., Wu, J., Li, X., Xu, F., & Yang, Y. (2023). Identification of the spatiotemporal variability and pollution sources for potential pollutants of the Malian River water in Northwest China using the PCA-APCS-MLR receptor model. Exposure and Health. https://doi.org/10.1007/s12403-023-00537-0

    Article  Google Scholar 

  • Mustapha, A., Aris, A. Z., Ramli, M. F., & Juahir, H. (2012). Temporal aspects of surface water quality variation using robust statistical tools. The Scientific World Journal, 2012, 294540. https://doi.org/10.1100/2012/294540

  • Narany, T. S., Ramli, M., & F., Aris, A. Z., Sulaiman, W. N. A., & Fakharian, K. (2014). Spatiotemporal variation of groundwater quality using integrated multivariate statistical and geostatistical approaches in Amol-Babol Plain. Iran. Environmental Monitoring and Assessment, 186, 5797–5815. https://doi.org/10.1007/s10661-014-3820-8

    Article  CAS  Google Scholar 

  • Nguyen, B. T., Nguyen, T. M. T., & Bach, Q. (2020). Assessment of groundwater quality based on principal component analysis and pollution source-based examination: A case study in Ho Chi Minh City. Vietnam. Environmental Monitoring and Assessment, 192, 395. https://doi.org/10.1007/s10661-020-08331-0

    Article  CAS  Google Scholar 

  • Papaioannou, A., Mavridou, A., Hadjichristodoulou, C., Papastergiou, P., Pappa, O., Dovriki, E., & Rigas, I. (2010). Application of multivariate statistical methods for groundwater physicochemical and biological quality assessment in the context of public health. Environmental Monitoring and Assessment, 170, 87–97. https://doi.org/10.1007/s10661-009-1217-x

    Article  CAS  Google Scholar 

  • Patil, V. B. B., Pinto, S. M., Govindaraju, T., Hebbalu, V. S., Bhat, V., & Kannanur, L. N. (2019). Multivariate statistics and water quality index (WQI) approach for geochemical assessment of groundwater quality-A case study of KanaviHalla Sub-Basin, Belagavi, India. Environmental Geochemistry and Health, 42, 2667–2684. https://doi.org/10.1007/s10653-019-00500-6

    Article  CAS  Google Scholar 

  • Ram, A., Tiwari, S. K., Pandey, H. K., Chaurasia, A. K., Singh, S., & Singh, Y. V. (2021). Groundwater quality assessment using water quality index (WQI) under GIS framework. Applied Water Science, 11, 46. https://doi.org/10.1007/s13201-021-01376-7

    Article  CAS  Google Scholar 

  • Rao, V. V. S. G., Rao, G. T., Surinaidu, L., Mahesh, J., Rao, S. T. M., & Rao, B. M. (2013). Assessment of geochemical processes occurring in groundwaters in the coastal alluvial aquifer. Environmental Monitoring and Assessment, 185, 8259–8272. https://doi.org/10.1007/s10661-013-3171-x

    Article  CAS  Google Scholar 

  • Reghunath, R., Murthy, T. R. S. S., & Raghavan, B. R. (2002). The utility of multivariate statistical techniques in hydrogeochemical studies: An example from Karnataka. India. Water Research, 36(10), 2437–2442. https://doi.org/10.1016/S0043-1354(01)00490-0

    Article  CAS  Google Scholar 

  • Sahour, H., Gholami, V., & Vazifedan, M. (2020) Comparative analysis of statistical and machine learning techniques for mapping the spatial distribution of groundwater salinity in a coastal aquifer. Journal of Hydrology, 591, 125321. https://doi.org/10.1016/j.jhydrol.2020.125321

  • Senthilkumar, G., Ramanathan, A. L., Nainwal, H. C., & Chidambaram, S. (2008). Evaluation of the hydro geochemistry of groundwater using factor analysis in the Cuddalore coastal region, TamilNadu. India. Indian Journal of Marine Sciences, 37(2), 181–185.

    CAS  Google Scholar 

  • Singha, S., Pasupuleti, S., Singha, S.S., Singh, R., & Kumar, S. (2021). Prediction of groundwater quality using efficient machine learning technique. Chemosphere, 276, 130265. https://doi.org/10.1016/j.chemosphere.2021.130265

  • Solangi, S. G., Siyal, A. A., Babar, M. M., & Siyal, P. (2019). Application of water quality index, synthetic pollution index, and geospatial tools for the assessment of drinking water quality in the Indus Delta. Pakistan. Environmental Monitoring and Assessment, 191, 731. https://doi.org/10.1007/s10661-019-7861-x

    Article  CAS  Google Scholar 

  • Taşan, M., Demir, Y., & Taşan, S. (2022). Groundwater quality assessment using principal component analysis and hierarchical cluster analysis in Alaçam. Turkey. Water Supply, 22(3), 3431–3447. https://doi.org/10.2166/ws.2021.390

    Article  CAS  Google Scholar 

  • Todd, K. D., & Mays, W. L. (2005). Groundwater hydrology. third ed. John Wiley and Sons.

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

    Article  CAS  Google Scholar 

  • Troudi, N., Hamzaoui-Azaza, F., Tzoraki, O., Melki, F., & Zammouri, M. (2020). Assessment of groundwater quality for drinking purpose with special emphasis on salinity and nitrate contamination in the shallow aquifer of Guenniche (Northern Tunisia). Environmental Monitoring and Assessment, 192, 641. https://doi.org/10.1007/s10661-020-08584-9

    Article  CAS  Google Scholar 

  • Ustaoglu, F., Tepe, Y., & Tas, B. (2020). Assessment of stream quality and health risk in a subtropical Turkey river system: A combined approach using statistical analysis and water quality index. Ecological Indicators, 113, 105815. https://doi.org/10.1016/j.ecolind.2019.105815

  • Uyanik, G. K., & Güler, N. (2013). A study on multiple linear regression analysis. Procedia - Social and Behavioral Sciences, 106, 234–240. https://doi.org/10.1016/j.sbspro.2013.12.027

    Article  Google Scholar 

  • Valentini, M., dos Santos, G. B., & Vieira, B. M. (2021). Multiple linear regression analysis (MLR) applied for modeling a new WQI equation for monitoring the water quality of Mirim Lagoon, in the state of Rio Grande do Sul-Brazil. SN Applied Sciences, 3, 70. https://doi.org/10.1007/s42452-020-04005-1

  • Wang, H., Chen, Q., Wei, J., & Ji, Y. (2020a). Geochemical characteristics and influencing factors of groundwater Fe in seawater intrusion area. Water, Air, & Soil Pollution, 231, 348. https://doi.org/10.1007/s11270-020-04724-6

    Article  CAS  Google Scholar 

  • Wang, D., Wu, J., Wang, Y., & Ji, Y. (2020b). Finding high-quality groundwater resources to reduce the hydatidosis incidence in the Shiqu County of Sichuan Province, China: Analysis, assessment, and management. Exposure and Health, 12, 307–322. https://doi.org/10.1007/s12403-019-00314-y

    Article  CAS  Google Scholar 

  • WHO (2011). Guidelines for drinking water quality. Fourth Edition, World Health Organization.

  • Wu, J., Li, P., Wang, D., Ren, X., & Wei, M. (2020). Statistical and multivariate statistical techniques to trace the sources and affecting factors of groundwater pollution in a rapidly growing city on the Chinese Loess Plateau. Human and Ecological Risk Assessment: An International Journal, 26(6), 1603–1621. https://doi.org/10.1080/10807039.2019.1594156

    Article  CAS  Google Scholar 

  • Yang, W., Zhao, Y., Wang, D., Wu, H., Lin, A., & He, L. (2020). Using principal components analysis and IDW interpolation to determine spatial and temporal changes of surface water quality of Xin’anjiang River in Huangshan, China. International Journal of Environmental Research and Public Health, 17, 2942. https://doi.org/10.3390/ijerph17082942

    Article  CAS  Google Scholar 

  • Zeinalzadeh, K., & Rezaei, E. (2017). Determining spatial and temporal changes of surface water quality using principal component analysis. Journal of Hydrology: Regional Studies, 13, 1–10. https://doi.org/10.1016/j.ejrh.2017.07.002

    Article  Google Scholar 

  • Zhang, H., Cheng, S., Li, H., Fu, K., & Xu, Y. (2020). Groundwater pollution source identification and apportionment using PMF and PCA-APCA-MLR receptor models in a typical mixed land-use area in Southwestern China. Science of The Total Environment, 741, 140383. https://doi.org/10.1016/j.scitotenv.2020.140383

Download references

Acknowledgements

The authors thank Mr. Haripada Maity, Lab. Chem., Drinking Water Test Dep., Contai Sub-div. PHED, Gov. West Bengal and Mr. Ganesh Dinda, Jr. Eng., I&WD, Digha Irrig. Sect., Gov. West Bengal, for providing relevant data.

Author information

Authors and Affiliations

  1. School of Water Resources Engineering, Jadavpur University, Kolkata, 700032, West Bengal, India

    Chinmoy Ranjan Das & Subhasish Das

  2. Civil Engineering Department, Global Institute of Science & Technology, Purba Medinipur, Haldia, 721657, West Bengal, India

    Chinmoy Ranjan Das

  3. Ambuja Cement Ltd, Kolkata, 700019, West Bengal, India

    Souvik Panda

Authors
  1. Chinmoy Ranjan Das
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Subhasish Das
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Souvik Panda
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization and methodology: Chinmoy Ranjan Das and Subhasish Das; data collection: Souvik Panda; formal analysis: Chinmoy Ranjan Das; investigation: Chinmoy Ranjan Das and Subhasish Das; writing—original draft preparation: Chinmoy Ranjan Das; writing (review and editing) and supervision: Subhasish Das.

Corresponding author

Correspondence to Subhasish Das.

Ethics declarations

Ethical approval

The authors declare that they will follow the journal’s guidelines on the reliability of the scientific record.

Consent to participate

Not applicable

Consent for publication

Not applicable

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Das, C.R., Das, S. & Panda, S. MLR index–based principal component analysis to investigate and monitor probable sources of groundwater pollution and quality in coastal areas: a case study in East India. Environ Monit Assess 195, 1158 (2023). https://doi.org/10.1007/s10661-023-11804-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-023-11804-7

Keywords

Search

Navigation