A Quantitative Microbial Risk Assessment Associated with Cross-Connections in the Drinking Water Network in Combination with Hydraulic Modeling

Sammanfattning: Drinking water companies have the technology and responsibility to deliver safe and high-quality drinking water to the water distribution systems network (WDN). However, many events within the WDN, such as cross-connections and backflow, might degrade water quality and pose public health risks to consumers. Cross-connection and backflow events may occur if there is physical contact between the external non-potable water source and the drinking water. When the pressure in the external source is greater than in the WDN, and when there are inadequate cross-connections controls, cross-connections and backflows may occur. This project aimed to investigate the circumstances that influence cross-connection and backflow events and estimate the health risk of infection. The method used for this study included hydraulic and water quality modeling EPANET to simulate the fate and transport of pathogens in the WDN during the outbreak. Besides, the quantitative microbial risk assessment QMRA was used to evaluate the health risks associated with cross-connections and backflow events due to ingestion of contaminated water. The modeled events included four reference pathogens (viruses: Norovirus and Rotavirus, bacteria: Campylobacter, and protozoa: Cryptosporidium) from four water types (wastewater, greywater, treated wastewater, and treated greywater). The simulation considered three potential pathogen load risk levels entering WDN: extreme, evaluated, and endemic. The results indicate that the factors that influence pathogen intrusion and consequently the risk of infection were the duration and intensity of the low-pressure event, the location of the cross-connection, and the pathogen concentration in water sources. The estimated daily risk of infection from cross-connection and backflow events generally exceeded the acceptable target level of 10−6 per person per day for all reference pathogens and modeled events. The exception was for the endemic risk level during the cross-connections with treated wastewater and greywater, where the risk was 10−7 and 10−10. Several measures can be implemented to manage and mitigate the risk of cross-connections, such as demanding plumbing installation procedures and backflow prevention devices and developing an early detection system to predict the cross-connection earlier before the outbreak happens to the system, for instance, by applying a machine learning system.