Developing real time operating rules for trading discharge permits in rivers: Application of Bayesian Networks

Discharge permit trading programs show potential as cost-effective methods of pollution control. This study focuses on developing real time operating rules for trading discharge permits in rivers. In this study, Trading Ratio System (TRS) suggested by Hung and Shaw (2005) is extended to be applicable to Biochemical Oxygen Demand (BOD)/Dissolved Oxygen (DO) management in rivers. The Extended Trading Ratio System (ETRS) is used in a Monte Carlo Analysis to provide the required data for training a Bayesian Network (BN). Therefore, the existing uncertainties in the model input variables are incorporated. Low water quality is also considered as a fuzzy event and fuzzy risk of violating the water quality standards are estimated at checkpoints along the river. The trained BNN can be used for real time river water quality management and provides the probability distributions functions of treatment levels and trading discharge permit policies. The methodology is successfully applied to the Zarjub River in the northern part of Iran to show its usefulness as a cost-effective and risk-informed decision-making tool in real-time river water quality management.