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Assessment of the Eutrophication-Related Environmental Parameters in Two Mediterranean Lakes by Integrating Statistical Techniques and Self-Organizing Maps

Author

Listed:
  • Ekaterini Hadjisolomou

    (Laboratory of Marine Geology and Physical Oceanography, Department of Geology, Patras University, 26504 Patras, Greece)

  • Konstantinos Stefanidis

    (Department of Biology, University of Patras-University Campus Rio, 26500 Patras, Greece
    Sector of Water Resources and Environmental Engineering, School of Civil Engineering, National Technical University of Athens, 15780 Athens, Greece)

  • George Papatheodorou

    (Laboratory of Marine Geology and Physical Oceanography, Department of Geology, Patras University, 26504 Patras, Greece)

  • Evanthia Papastergiadou

    (Department of Biology, University of Patras-University Campus Rio, 26500 Patras, Greece)

Abstract

During the last decades, Mediterranean freshwater ecosystems, especially lakes, have been under severe pressure due to increasing eutrophication and water quality deterioration. In this article, we compared the effectiveness of different data analysis methods by assessing the contribution of environmental parameters to eutrophication processes. For this purpose, principal components analysis (PCA), cluster analysis, and a self-organizing map (SOM) were applied, using water quality data from two transboundary lakes of North Greece. SOM is considered as an advanced and powerful data analysis tool because of its ability to represent complex and nonlinear relationships among multivariate data sets. The results of PCA and cluster analysis agreed with the SOM results, although the latter provided more information because of the visualization abilities regarding the parameters’ relationships. Besides nutrients that were found to be a key factor for controlling chlorophyll-a (Chl - a), water temperature was related positively with algal production, while the Secchi disk depth parameter was found to be highly important and negatively related toeutrophic conditions. In general, the SOM results were more specific and allowed direct associations between the water quality variables. Our work showed that SOMs can be used effectively in limnological studies to produce robust and interpretable results, aiding scientists and managers to cope with environmental problems such as eutrophication.

Suggested Citation

  • Ekaterini Hadjisolomou & Konstantinos Stefanidis & George Papatheodorou & Evanthia Papastergiadou, 2018. "Assessment of the Eutrophication-Related Environmental Parameters in Two Mediterranean Lakes by Integrating Statistical Techniques and Self-Organizing Maps," IJERPH, MDPI, vol. 15(3), pages 1-16, March.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:3:p:547-:d:136925
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    References listed on IDEAS

    as
    1. Binwu Wang & Hong Li & Danfeng Sun, 2014. "Social-Ecological Patterns of Soil Heavy Metals Based on a Self-Organizing Map (SOM): A Case Study in Beijing, China," IJERPH, MDPI, vol. 11(4), pages 1-21, March.
    2. Kostas Moustris & Ioanna Larissi & Panagiotis Nastos & Athanasios Paliatsos, 2011. "Precipitation Forecast Using Artificial Neural Networks in Specific Regions of Greece," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(8), pages 1979-1993, June.
    3. Yan An & Zhihong Zou & Ranran Li, 2016. "Descriptive Characteristics of Surface Water Quality in Hong Kong by a Self-Organising Map," IJERPH, MDPI, vol. 13(1), pages 1-13, January.
    4. Oh, Hee-Mock & Ahn, Chi-Yong & Lee, Jae-Won & Chon, Tae-Soo & Choi, Kyung Hee & Park, Young-Seuk, 2007. "Community patterning and identification of predominant factors in algal bloom in Daechung Reservoir (Korea) using artificial neural networks," Ecological Modelling, Elsevier, vol. 203(1), pages 109-118.
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    1. Dong-Kyun Kim & Hyunbin Jo & Inwoo Han & Ihn-Sil Kwak, 2019. "Explicit Characterization of Spatial Heterogeneity Based on Water Quality, Sediment Contamination, and Ichthyofauna in a Riverine-to-Coastal Zone," IJERPH, MDPI, vol. 16(3), pages 1-17, January.

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