A review of water quality management system for protection of aquatic life : Hong Kong and international practices

Abstract

Due to the water pollution problem associated with human activities, a well-established water quality management (WQM) system is necessary for the protection of aquatic environments. Water Quality Objectives (WQOs), as one of the essential elements in WQM, serve as the science-based threshold levels and guidance values of physical, chemical, and biological parameters to control the pollution activities and to protect aquatic life. In this literature review, four conventional approaches for WQOs derivation, including background concentration approach, Assessment Factor (AF) approach, Species Sensitivity Distribution (SSD) approach, and Ecological Risk Assessment (ERA) approach, are introduced. The uses, advantages, and limitations of these four approaches are described, contrasted and discussed. Besides WQOs, water resources management is also important in WQM. Herein, five conventional approaches for water resources management, including technology-based approach, use-protection approach, non-degradation approach, screening approach and Water Quality Index (WQI) are highlighted. Each approach has its own applicability and merit. The uses of different approaches should be chosen carefully in order to achieve the protection goal of the aquatic environment. The WQM practices currently adopted in different parts of the world are still far from perfect. The future trends in WQM are also suggested in this dissertation. I have also performed a literature review on the current WQM system in Hong Kong and suggested some areas for improvements. Cluster analysis on the actual water quality data of Hong Kong (watercourses in Tolo Habour and Channel WCZ as an example) was carried out based on the temporal and spatial variations of the selected water quality parameters. The analysis results suggest that there is an opportunity to optimize the current water quality monitoring programme of Hong Kong by reducing the monitoring frequency and the number of monitoring sites so that the resources for water monitoring can be reduced without the loss of water quality information. The results also show that the cluster analysis is an effective statistical method to interpret complex water quality data and is a useful tool in WQM.