An empirical model for prediction of lake water suspended particulate matter

It is of fundamental importance in lake mass balance modelling to distinguish between the dissolved and particulate fractions. To do this, the suspended particulate matter concentration (SPM) is needed as well as measured or modelled values of the partition coefficient (Kd). A regression model for SPM based on data from 26 European lakes covering a wide limnological range is presented. The model yields an r2-value of 0.87. It predicts lake typical SPM values from lake total phosphorous concentration (TP), reflecting the influence of bioproduction on SPM, pH, reflecting allochthonous and autochthonous influences on SPM and the dynamic ratio (DR), a morphometric parameter reflecting the influence of resuspension on SPM. The model is shown to be stable, easy to use, and since the model parameters have a wide range, the model can be very useful in predictive lake modelling.