Using Non-supervised Artificial Neural Network for Determination of Anthropogenic Disturbance in a River System

Abstract

The study of river water quality plays an important role in assessing the pollution status and health of the water bodies. Human-induced activities such as domestic activities, aquaculture, agriculture and industries have detrimentally affected the river water quality. Pinang River is one of the important rivers in Balik Pulau District that supplies freshwater for human consumption. A total of 442 physical and chemical parameters data of the Pinang River, Balik Pulau catchment were analysed to determine the sources of pollutants entering the river. Non-supervised artificial neural network (ANN) was employed to classify and cluster the river into upstream, middle-stream and downstream zones. The monitored data and non-supervised ANN analysis demonstrated that the source of nitrate was derived from the upper part of the Pinang River, Balik Pulau while the sources of nitrite, ammonia and ortho-phosphate are predominant at the middle-stream of the river system. Meanwhile, the sources of high total suspended solid and biological oxygen demand were concentrated at the downstream of the river.