MODELS TO PREDICT ORGANIC CONTENT OF LAKE-SEDIMENTS

The aim of this study is to quantify and rank variables of significanc e to predict mean organic content (IG, loss on ignition) of surficial (0-1 cm) lake sediments in small glacial lakes. Various hypotheses con cerning the factors regulating IG in lakes were formulated and tested. Different statistical tests were used to separate random influences f rom causal influences. The best model provides an r(2)-value (r = the correlation coefficient) of 0.83 when model data are compared to empir ical data. This model is based on five readily available, standard map parameters: the percent of till and mires in the drainage area, the s ize and relief of the catchment, and the volume development (= the for m factor), linked to resuspension and form and size of the lake. Each of these variables only provides a limited degree of (statistical) exp lanation of the variability in IG among the lakes. The predictability of the model can not be improved by accounting for the zonation proble m, (i.e., the distribution of the characteristics in the drainage area , as given by the Drainage Area Zonation-method, DAZ), or for water ch emical variables (pH, alkalinity, conductivity, total-P, colour, etc.) . The model allows mean values of IG to be estimated from readily avai lable data of ''geological'' characteristics of the lake and its drain age area. The variability in IG from other factors/variables, such as specific anthropogenic sources, etc. may then be quantitatively differ entiated from the impact of these ''geological'' factors. These predic tive models are, to the best of the author's knowledge, the first ever to be presented for IG. These empirical models can only, however, be used to predict IG for lakes of the same lake type, and for lakes with model variables within the range of the given model variables.