Risk Based Analysis for Contamination Event Selection and Optimal Sensor Placement for Intermittent Water Distribution Network Security

Abstract

Water distribution networks are vulnerable to various contamination events that may be accidental or purposeful. Sensors are required for online monitoring of water quality to safeguard human health. Since sensors are costly, their numbers must be limited that makes sensor locations crucial in the water monitoring system. This paper aims at location of sensors in intermittent water distribution system which are more prone to accidental contamination due to contaminants ingress into the pipe lines because of low pressures during non supply hours. Considering deployment of limited number of sensors, the novelty of the paper is to propose a methodology for selection of contamination events with associated risk to be used in design of sensor network. Integrated risk assessment model is used to identify risk prone areas that may lead to possible contamination events. A Genetic Algorithm based methodology is suggested for optimal location of water quality sensors to maximize the detection likelihood of the contamination events within the acceptable time from the risk prone areas to improve network security. A comparison of sensor network design is made by considering contamination events occurring with: (i) equal probability at all the nodes; (ii) equal probability at risk prone nodes; and (iii) probability of occurrences based on quantified risk, to show that identification of risk prone areas and selection of contamination events results in reduction of computational work and more sensible placement of sensors.