Presentation and analysis of a model simulating the pH response of lake liming

Lake liming is a very common remedy for acidification in Sweden. This study presents a practically useful management model to plan and predict the outcome and duration of the liming. It is a mixed model including both statistical regressions, based on catchment and lake morphometric data, and dynamic, mass-balance interactions. It is driven by data on the amount of lime and the month of liming. A submodel estimates a natural pH, since it is important not to lime to a higher pH than the natural. The liming model is very easy to handle since all the input data can be obtained from maps and no field measurements are necessary. In this paper, the model is presented and the calibration and validation processes are thoroughly examined. The model, which is the first of its kind, has been validated against an independent set of data from eight Swedish lakes. The predictive power of the model has been tested in different ways and it can be concluded that the predictive success is such that the model should be very useful for lake management to optimise lake liming. This model can be regarded as a significantly improved tool for lake liming compared to the very simplistic tables used today, or as a significantly simplified model compared to the existing very extensive models, which are not generally used in practical planning of lake liming operations since such models are driven by many lake-specific variables which are difficult and expensive to access.