Factor analytical study on water quality in Lake Saimaa, Finland

Multivariate data analysis methods (4-way Candecomp-PARAFAC: model solved w ith Multilinear Engine (ME-1)) were used to interpret the data of over two decades to study the changes in the water of Lake Saimaa in Finland. Earlie r studies have shown that it is difficult to extract the natural background from the other sources of variation. By using the multilinear model three interpretable factors representing natural and anthropogenic processes coul d be extracted. The natural long-term variation, seasonal fluctuation and d ilution of discharges in the recipient area could be extracted into their o wn factors, which could be easily visualized. The variation could be also p resented with estimated variation in the water quality parameters caused by each of these natural or anthropogenic processes.