Positioning, within water distribution networks, of monitoring stations aiming at an early detection of intentional contamination.

A stochastic approach is proposed, aiming at the optimal allocation of increasing sets of monitoring stations for the early detection of the intentional contamination of water distribution networks. The approach is based on the use of the Monte Carlo technique for the generation of a number of time-varying hydraulic scenarios, each consisting of a succession of steady conditions related to different users’ water demands. Given a time-varying hydraulic scenario, and chosen an injection node, the spreading of the contaminant through the network is evaluated by means of a lagrangian advection model, and the arrival time to all the potential monitoring stations are calculated. If these operations are accomplished for all the source nodes, and for each of the time-varying hydraulic scenarios, a statistical analysis allows for the allocation of the monitoring stations which maximize the number of upstream nodes characterized by arrival times less than a pre-assigned value (Early Warning Time, EWT).