Spatial Assessment of Water Quality Patterns using Environmetric Techniques: A Case Study in Muda River Basin (Malaysia)

Abstract

River pollution impact human health, environment and the sustainable development. This study was conducted to identify spatial patterns and the main parameters affecting the water pollution within nine monitoring stations in the Muda River basin (Malaysia) over a 16-year database (1998–2013). Environmetric techniques were applied to the dataset. These combined Cluster Analysis, Discriminant Analysis, and Multiple Linear Regression. The Cluster Analysis showed that the monitoring stations divided into two separate groups based on similarities features of water quality while Discriminant Analysis validated these groups. Furthermore, the Multiple Linear Regression analysis showed that the significant parameters contributing to variability the Water Quality Index was biological oxygen demand, chemical oxygen demand and ammonia nitrogen. This was due to the point-source pollution, particularly from rubber factory. Therefore, the results provided information to support future water pollution control strategies.