Importance Sampling of Water Distribution System Contamination Events Based on Nodal Neighborhood Populations

A goal of water distribution system security is to ensure that clean water is delivered to consumers. Potential for contaminations and cross connections make it difficult to ensure that the water being delivered to consumers is truly of high quality. The placement of water quality monitoring stations within a WDS system has proven a successful method to prevent the delivery of contaminated water. The locations of monitoring stations in a WDS is critical to the performance of a water quality monitoring station network (early warning system or EWS); ideally sensors will be placed at a limited number of locations which can quickly detect all contamination events. Designing a EWS to protect against every possible contamination event is computationally infeasible; however it is crucial that high impact contamination events will be detected. In this study a contamination event is defined as an intrusion taking place at a specific junction and time in a WDS. A probability distribution is generated according to the portion of a network's population served by water that flows "downstream" from a specific junction at a specific time, within a defined interval of time; this portion of population would be most at risk to exposure of the corresponding junction and time. The newly generated probability distribution is then used for sampling a set of contamination events used to design an EWS. The downstream nodes are calculated using breadth first search and the nodal populations are calculated according to the temporal demands. The relative consequence of a junction being contaminated is calculated using steady state and dynamic hydraulic models; elevating the need to perform numerous complex water quality simulations. Monitoring station networks designed using the proposed importance sampling technique and traditional random sampling are compared.