Propagation of Chlorine Demand Signals Induced by Microbial Contaminants in a Drinking Water Distribution System

Chlorine residual concentration is used as a protection from accidental and intentional intrusion of microbial contaminants in distribution systems. Monitoring chlorine residual with real-time sensors may enable detection of such intrusions. However, this necessitates prediction of chlorine levels and how they change under normal conditions and in the event of a microbial intrusion event. Existing multispecie models require knowledge of specific reaction kinetics between chlorine and complex cellular matrices that are unlikely to be known a priori. Rather, we propose utilization of a parallel first order rate expression describing microbially-induced chlorine decay over a wide range of conditions. The model can be parameterized using a limited number of batch experiments. The model formulation is then integrated into EPANET-MSX using the programmer's toolkit. We present simulations of a series of microbial events in a small distribution system using the model. Our results indicate that change in residual induced by microbial intrusion events can be simulated in distribution system models. Chlorine residual signals can thus be predicted. Event detection is limited by lack of control of chlorine concentration at the time and location of the contaminant event, the unique species-specific chlorine reaction kinetics, and the changing demand patterns in the system.