Using mobile and fixed sensors for optimal monitoring of water distribution network under dynamic water quality simulations

Urban water distribution networks (WDNs) are strategic infrastructures, which have critical roles in preserving public health and social growth. This study designs a water quality monitoring network (WQMN) in the WDN Example 3 of EPANET2.0, contaminated with potassium cyanide (KCN), accounting for the dynamic changes of chlorine as a common water-quality parameter. The uncertainties in the contaminant events, such as the amount, location, start-time, and duration of contaminant injection, are considered in the problem formulations. A simulation-optimization framework based on EPANET-MSX and Particle Swarm Optimization algorithm is developed to determine the optimal location of the fixed sensor(s) and/or time and location of releasing mobile sensor(s). The results indicate that increasing the available mobile sensors from 1 unit to 3 or 5 units, decreased the contaminant detection time (DT) by 14% and 22%, increased the contaminant detection likelihood by 102% and 159%, and reduced the contaminated water consumption by 52% and 70%, respectively. The sensitivity analysis on the number of available sensors implies that changes in fixed sensors are more effective than mobile sensors on contaminant DT. The results showed the uncertainty in sink nodes' coverage area and mobile sensors' battery life become more important as the number of mobile sensors increases.

Automated summary

Urban water distribution networks play a critical role in preserving public health and social growth. This study designs a water quality monitoring network in a water distribution network contaminated with potassium cyanide, taking into account the dynamic changes in chlorine. A simulation-optimization framework is developed to determine the optimal location and time for fixed and mobile sensors, leading to improved contaminant detection and reduced contaminated water consumption.