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Multivariate analysis of water quality parameters in Lake Palic, Serbia

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Abstract

This study presents a comprehensive investigation of water quality parameters in the fourth sector of Lake Palic in Serbia, which has a regional strategic importance. Namely, it is designated as a tourist destination. What is perhaps even more important is that its surplus water ends up in Lake Ludas, a significant habitat for migrating and aquatic bird species, and it is a RAMSAR site. The conducted analysis points to the major conclusion that the reasons for very high Chlorophyll-a values can be found in considerable anthropogenic pressures exerted on the studied area. Due to these pressures, the lake is not in ecological equilibrium. To support this conclusion, an in-depth analysis was conducted using water quality measurements for 9 years, from 2011 to 2019. The data was subject to principal component analysis (PCA) and machine learning classification algorithms that identified a seasonal character regarding the lake’s water quality. Water quality indexes (WQI) were determined using two approaches to provide a more general insight into the lake’s overall quality. Keeping in mind the large number of data gathered monthly within the Palic-Ludas Lake system, fitted models for estimating certain water quality parameters were also developed. This was accomplished via multivariate regression, resulting in a number of equations that can, using a few basic input parameters, predict values of ammonium nitrogen, Chlorophyll-a, and 5-day biological oxygen demand. The fitted models were obtained for relatively homogeneous periods within a year identified by cluster analysis.

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References

  • Aliyu, G. A., Jamil, N. R. B., Adam, M. B., & Zulkeflee, Z. (2019). Assessment of Guinea Savanna River system to evaluate water quality and water monitoring networks. Global Journal of Environmental Science and Management, 5(3), 345–356.

    CAS  Google Scholar 

  • Bhateria, R., & Jain, D. (2016). Water quality assessment of lake water: A review. Sustainable Water Resource Management, 2, 161–173.

    Article  Google Scholar 

  • Bilgin, A. (2018). Evaluation of surface water quality by using Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) method and discriminant analysis method: A case study Coruh River Basin. Environmental Monitoring and Assessment, 190, 554.

    Article  Google Scholar 

  • Breiman, L. (2001). Random Forestes. Machine Learning, 45(1), 5–32.

    Article  Google Scholar 

  • Calazans, G. M., Pinto, C. C., da Costa, E. P., Perini, A. F., & Oliveira, S. C. (2018). The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin, Brazil. Environmental Monitoring and Assessment, 190, 491.

    Article  Google Scholar 

  • Canadian Council of Ministers of the Environment. (2001). Canadian Water Quality Guidelines for the Protection of Aquatic Life, CCME Water Quality index 1.0, User’s Manual. CCME, Winnipeg, Manitoba, Canada.

  • Canadian Council of Ministers of the Environment. (2012). Synthesis of Research and Application of the CCME Water Quality Index, CCME Project No. 520–2012. Malahat, British Columbia, Canada.

  • Chenini, I., & Khemiri, S. (2009). Evaluation of ground water quality using multiple linear regression and structural equation modeling. International Journal of Environmental Science and Technology, 6, 509–519.

    Article  CAS  Google Scholar 

  • Clesceri, L. S., Greenberg, A. E., & Eaton, A. D. (Eds.) (1999). Standard methods for the examination of water and wastewater, 20th edition. American Public Health Association (APHA), the American Water Works Association (AWWA), and the Water Environment Federation (WEF), Washington DC, USA.

  • Čoha, F. (1990). Voda za piće - Standardne metode za ispitivanje higijenske ipravnosti. Savezni zavod za zdravstvenu zaštitu, NIP Privredni pregled, Beograd (in Serbian).

  • Ewaid, S. H., & Al-Hamzawi, S. A. A. (2017). Water quality index for Al-Gharraf River, southern Iraq. Egyptian Journal of Aquatic Research, 43, 117–122.

    Article  Google Scholar 

  • Gradilla-Hernández, M. S., de Anda, J., Garcia-Gonzalez, A., Montes, C. Y., Barrios-Pina, H., Ruiz-Palomino, P., & Díaz-Vázquez, D. (2020). Assessment of the water quality of a subtropical lake using the NSF-WQI and newly proposed ecosystem specific water quality index. Environmental Monitoring and Assessment, 192, 296.

    Article  Google Scholar 

  • Horvat, M., & Horvat, Z. (2020). Implementation of a monitoring approach: The Palic-Ludas lake system in the Republic of Serbia. Environmental Monitoring and Assessment, 192, 150.

    Article  Google Scholar 

  • Horvat, Z., & Horvat, M. (2016). Two dimensional heavy metal transport model for natural watercourses. River Research and Applications, 32(6), 1327–1341.

    Article  Google Scholar 

  • Horvat, Z., Isic, M., & Spasojevic, M. (2015). Two dimensional river flow and sediment transport model. Environmental Fluid Mechanics, 15(3), 595–625.

    Article  Google Scholar 

  • Ji, X., Dahlgren, R. A., & Zhang, M. (2016). Comparison of seven water quality assessment methods for the characterization and management of highly impaired river systems. Environmental Monitoring and Assessment, 188, 15.

    Article  Google Scholar 

  • Kumar, P. (2019). Numerical quantification of current status quo and future prediction of water quality in eight Asian megacities: Challenges and opportunities for sustainable water management. Environmental Monitoring and Assessment, 191, 319.

    Article  Google Scholar 

  • Kumari, R., & Sharma, R. C. (2019). Assessment of water quality index and multivariate analysis of high altitude sacred Lake Prashar, Himachal Pradesh, India. International Journal of Environmental Science and Technology, 16, 6125–6134.

    Article  CAS  Google Scholar 

  • Li, Y. P., Tang, C. Y., Yu, Z. B., & Acharya, K. (2014). Correlations between algae and water quality: Factors driving eutrophication in Lake Taihu, China. International Journal of Environmental Science and Technology, 11, 169–182.

    Article  CAS  Google Scholar 

  • Liu, W. J., Li, Z. B., Zou, D. S., Ren, C. J., & Pei, Q. B. (2017). The characteristics and evaluation of water pollution in Ganjiang Tail River. IOP Conference Series: Earth and Environmental Science 82, IOP Publishing.

  • Lumb, A., Halliwell, D., & Sharma, T. (2006). Application of CCME water quality index to monitor water quality: A case study of the Mackenzie River Basin, Canada. Environmental Monitoring and Assessment, 113, 411–429.

    Article  CAS  Google Scholar 

  • Mohamed, I., Othman, F. N., Ibrahim, A. I., Alaa-Eldin, M. E., & Yunus, R. M. (2014). Assessment of water quality parameters using multivariate analysis for Klang River basin. Malaysia. Environmental Monitoring and Assessment, 187, 4182.

    Article  Google Scholar 

  • Omwene, P. I., Öncel, M. S., Celen, M., & Kobya, M. (2019). Influence of arsenic and boron on the water quality index in mining stressed catchments of Emet and Orhaneli streams (Turkey). Environmental Monitoring and Assessment, 191, 199.

    Article  Google Scholar 

  • Pastor, K. A., Acanski, M. M., Vujic, Dj. N., Jovanovic, Dj., & Wienkoop, S. (2016). Authentication of Cereal Flours by Multivariate Analysis of GC-MS Data. Chromatographia, 79(19–20), 1387–1393.

    Article  CAS  Google Scholar 

  • Satheeshkumar, P., & Khan, A. B. (2012). Identification of mangrove water quality by multivariate statistical analysis methods in Pondicherry coast, India. Environmental Monitoring and Assessment, 184, 3761–3774.

    Article  CAS  Google Scholar 

  • Sergeant, C. J., Starkey, E. N., Bartz, K. K., Wilson, M. H., & Mueter, F. J. (2016). A practitioners guide for exploring water quality patterns using principal components analysis and Procrustes. Environmental Monitoring and Assessment, 188, 249.

    Article  CAS  Google Scholar 

  • Solangi, G. S., 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.

    Article  CAS  Google Scholar 

  • Tavakoly, S. B., Monazami, G., & Borgheipour, H. (2019). Application of water quality indices for evaluating water quality and anthropogenic impact assessment. International Journal of Environmental Science and Technology, 16, 3001–3012.

    Article  Google Scholar 

  • Voudouris, K., & Voutsa, D. (2012). Water quality monitoring and assessment. InTech, Rijeka, Croatia.

  • Willcock, S., Martínez-López, J., Hooftman, D. A. P., Bagstad, K. J., Balbi, S., Marzo, A., Prato, C., Sciandrello, S., Signorello, G., Voigt, B., Villa, F., Bullock, J. M., & Athanasiadis, I. N. (2018). Machine learning for ecosystem services. Ecosystem Services, 33, 165–174.

    Article  Google Scholar 

  • Witten, I., Frank, E., Hall, M., & Pal, C. (2016). Data mining—Practical machine learning tools and techniques (4th ed.). Morgan Kaufmann.

    Google Scholar 

  • Yadav, S., Babel, M., Shrestha, S., & Deb, P. (2019). Land use impact on the water quality of large tropical river: Mun River Basin, Thailand. Environmental Monitoring and Assessment, 191, 614.

    Article  Google Scholar 

  • Yilma, M., Kiflie, Z., & Gessese, N. (2019). Assessment and interpretation of river water quality in Little Akaki River using multivariate statistical techniques. International Journal of Environmental Science and Technology, 16, 3707–3720.

    Article  CAS  Google Scholar 

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Funding

This work was funded by the Ministry of Education, Science and Technical Development of the Republic of Serbia.

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Authors and Affiliations

  1. Faculty of Civil Engineering Subotica, University of Novi Sad, Kozaracka 2a, 24000, Subotica, Serbia

    Mirjana Horvat & Zoltan Horvat

  2. Faculty of Technology Novi Sad, University of Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia

    Kristian Pastor

Authors
  1. Mirjana Horvat
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  2. Zoltan Horvat
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  3. Kristian Pastor
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Correspondence to Zoltan Horvat.

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Horvat, M., Horvat, Z. & Pastor, K. Multivariate analysis of water quality parameters in Lake Palic, Serbia. Environ Monit Assess 193, 410 (2021). https://doi.org/10.1007/s10661-021-09195-8

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