Session: 53, Room:
The main objective of this study was to assess the quality of water from five monitoring stations in Asopos River (central Greece), and evaluate the main factors that affect water quality. Fifty one biochemical parameters measured both in situ and in the laboratory three times a year for two consecutive years. Multivariate analysis of Hierarchical cluster analysis and Principal component analysis were used to interpret water quality characteristics. Cluster analysis grouped the samples in two main clusters (classes) corresponding to different main activities which affect water quality characteristics. The first cluster includes the two sampling stations located near the industrial areas and the second one the three stations located in areas affected by agricultural activities. Principal Component Analysis identified two factors which explain 84,5% of the variability of the original mean data set. The first factor explaining 50,5 % of the whole data variability related mainly to “chemical quality parameters”, while the second factor explaining 34% of total data variability related mainly to “biological quality parameters”. This study showed that multivariate statistical techniques proved effective in river water quality classification based on large and complex water quality data sets.
Sat, 09/07/2019 - 16:30 to 16:33
Flash presentation in Lakes, rivers, estuaries and ecosystem health