A FRAMEWORK TO SUPPORT DECISION MAKING IN WATER QUALITY MODELLING

The US Geological Survey Virtual Beach (VB) framework was developed to convert water quality data into useful regression algorithms to support the monitoring, planning and forecasting of water quality issues in beaches. The VB has been successfully used in different parts of the world in providing solutions to water quality problems. VB is based on Multi-Linear Regression Approach and its ability to transform non-linear datasets using functions such as square root, square, log and natural logs into linear forms given its advantage in the development of useful statistically based algorithms for making decisions in water resources management. In this study, the VB was applied to develop useful empirical regression expressions to support the monitoring and forecasting of five-day Biological Oxygen Demand (BOD5), Total Phosphorus (TP) and Ammonium Nitrogen (NH3-N) conducted under the bacterial technology experiments applied in some parts of China. The case studies indicate the VB framework’s feasibility to develop empirical expressions to support water quality modelling in a broad perspective.