Forecasting physicochemical variables by a classification tree method. Application to the Berre Lagoon (south France).

Abstract

The dynamics of the "Etang de Berre", a brackish lagoon situated close to the French Mediterranean sea coast, is strongly disturbed by freshwater inputs coming from an hydroelectric power station. The system dynamics has been described as a sequence of daily typical states from a set of physicochemical variables such as temperature, salinity and dissolved oxygen rates collected over three years by an automatic sampling station. Each daily pattern summarizes the evolution, hour by hour of the physicochemical variables. This article presents results of forecasts of the states of the system subjected to the simultaneous effects of meteorological conditions and freshwater releases. We recall the main step of the classification tree method used to build up the predictive model (Classification and Regression Trees, Breiman et al., 1984) and we propose a transfer procedure in order to test the stability of the model. Results obtained on the Etang de Berre data set allow us to describe and predict the effects of the environmental variables on the system dynamics with a margin of error. The transfer procedure applied after the tree building process gives a maximum gain in prediction accuracy of about 15%.