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

Ekaterini Hadjisolomou, Konstantinos Stefanidis, George Papatheodorou and Evanthia Papastergiadou
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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
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

IJERPH, 2018, vol. 15, issue 3, 1-16

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.

Keywords: PCA; cluster analysis; self-organizing map; neural networks; nutrients; Mediterranean lakes (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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