A model to predict how individual factors influence Secchi depth variations among and within lakes

This work presents a model to predict lake Secchi depth. It has been developed as a part of a comprehensive ecosystem model, LakeWeb. The Secchi depth model is based on a modelling technique using dimensionless moderators. It gives, e.g., weekly variations and accounts for how various factors influence Secchi depth individually in spite of the fact that many of them are interrelated in a complex manner. The model has been tested over a wide range of lakes. It gives predictions that agree well with empirical reference regressions, and also expected and requested divergences when the regressions do not provide sufficient resolution. The model is driven by the following data which are easily accessed from standard monitoring programs or maps: Total phosphorus, colour, pH, mean depth and lake area reflecting the three main processes influencing variations of Secchi depth within and among lakes, allochthonous inputs, autochthonous production and resuspension.