Evaluation of river water quality by multidimensional analysis using parameters characteristic of dissolved organic matter
Satisfactory systems for evaluating river water quality have not yet been established. In France, as in many other European countries, water quality is evaluated using physico-chemical or biological parameter grids. This method implicitly assumes that these parameters are independent from each other and that a universal state of reference exists. In fact, when taking into account the great diversity of rivers it is clear that any evaluation of water quality requires that reference conditions be specified for each water system. Although it is one of the objectives of the new European Water Framework Directive, this problem has not yet been resolved. In addition, it is important to note that the state of water is characterised by dependent analytical parameters, and that the relationships linking these parameters evolve with the state of the water; this variable dependence must be taken into account. Lastly, it is important to note that organic matter is generally underestimated by current water quality evaluation systems. In the present study an attempt was made to evaluate the water quality of the Vienne River situated in western France. This study provided us with the opportunity to verify the accuracy of the current system. A monthly analytical monitoring program at eight study sites was carried out during the period 1999-2001. It allowed us to demonstrate that the well-known method of the principal component analysis (PCA), together with correlation analysis, was an appropriate tool for this purpose. More specifically, we showed that when using parameters characteristic of organic matter, this tool is well adapted for monitoring spatial and temporal changes in water quality. As this method is graphical, it made the choice of a reference point possible. This study showed that traditional parameters currently used, which are primarily inorganic, were not sufficient to identify anthropogenic contributions. For this reason we used unconventional organic variables, formerly used to study the structure of the dissolved organic matter (DOM) in surface waters, such as: - the distribution of the various organic fractions, such as humic (or hydrophobic) substances and non humic (or hydrophilic) substances, after filtration through macroporous XAD8 and XAD4 resins, under well-defined conditions; - the distribution of the apparent molecular weights, by ultrafiltration through membranes with molecular weight cut-offs of 30, 10 and 3 kDaltons; - fluorescence spectrometry; - the ratio UV-absorbance at 254 nm/dissolved organic carbon (SUVA). It was noted in this study that these organic variables, coupled with those classically analysed (Chemical Oxygen Demand, COD; Biological Oxygen Demand, BOD5), were often mainly responsible for the variations in the water quality. Principal Component Analysis was used to extract the main factors associated with water quality variability. The graphical representation obtained underlined that the greatest variability of the points characteristic of the stations could be observed on the first principal component. This component was linked to the organic variables. The second principal component was linked to inorganic variables indicative of the geological substrate. In addition, it was shown that the temporal dispersion of stations in the PCA graphical representation can be used to evaluate (either from the variance of the PCA factors, or from the box plots of these same factors) the disturbances related to the contributions of anthropogenic origin. The proportion of variability in water quality due to hydrological conditions could be also highlighted by PCA.