The use of a neural network technique for the prediction of water quality parameters

This paper is concerned with the use of Neural Network models for the prediction of water quality parameters in rivers. The procedure that should be followed in the development of such models is outlined. Artificial Neural Networks (ANNs) were developed for the prediction of the monthly values of three water quality parameters of the Strymon river at a station located in Sidirokastro Bridge near the Greek–Bulgarian borders by using the monthly values of the other existing water quality parameters as input variables. The monthly data of thirteen parameters and the discharge, at the Sidirokastro station, for the time period 1980–1990 were selected for this analysis. The results demonstrate the ability of the appropriate ANN models for the prediction of water quality parameters. This provides a very useful tool for filling the missing values that is a very serious problem in most of the Greek monitoring stations.