Analysis of oxygen rate time series in a strongly polluted lagoon using a regression tree method

This article presents results on daily forecasts of dissolved oxygen rates in a lagoon, the ‘Etang de Berre’, situated close to the French Mediterranean sea coast and submitted to particular meteorological conditions and freshwater inputs. To provide estimates of the response variable y (dissolved oxygen), a set of jointed decision rules is constructed by successive binary splitting of the predictor space composed of wind speed and freshwater flow data. The prediction model is displayed in the shape of a binary decision tree. We propose a transfer procedure in order to improve the prediction error of the tree model. Results obtained on the ‘Etang de Berre’ data set allow to describe and precise the effects of the environmental variables on the dissolved oxygen dynamics. The transfer procedure applied after the tree building process gives gains of prediction accuracy of about 17%.