Abstrakt

The study was undertaken to thoroughly characterise the contamination of water in industrially influenced river Klodnica, in order to explore monitoring strategies in case of limited analytical capacity. Statistical analysis undertaken after a short study was found to be helpful in reducing monitoring efforts in the future.Klodnica river is located within area of dominating coal mining, metallurgy, and additionally being influenced by chemical industry and a metropolitan area sewage contamination (Silesia industrial district in Poland). Thus, it is representative for heavily industrially influenced rivers in other areas of the world, including developing countries, where environmental monitoring has very limited resources. The data collected encompass 4-seasonal and catchment-wide (25 sampling locations) variability of contaminants, thus taking into account many sources influencing the pollution of riverine water (e.g. coal mines, chemical factories, steelworks or urban sewage).The list of variables described in the study comprises of pH, EC, 4 organic pollutants, 7 inorganic anions, 6 inorganic cations and 25 metals. Among those, statistically significant correlations were found in 543 cases (p<0.05) out of 1806 possibilities (correlations with Sn excluded because of no occurrence of this metal in samples). This gave a strong basis for searching for prediction of chosen variables by other variables. By means of cluster analysis closely related variables were chosen to form between 5 and 17 groups (fig. 1), which were then tested for possibilities of being replaced by one or two variables from the group. Regression models were used to achieve that.

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