Using graph theory for determining grab sampling location in real time upon a contamination detection in water distribution system

Ensuring the distribution of high-quality water from various sources to consumers via water distribution systems (WDS) is critical for guaranteeing public health. While standard water quality parameters are monitored at waterworks, it is still a challenge to monitor water quality in the WDS itself. A large body of research has investigated where to place online quality sensors in a WDS to detect deterioration in water quality. This study expands prior studies and aims to develop a methodology to determine the location of mobile sensor equipment to monitor water quality change in real-time at strategically important nodes in the water network. A graph-theory algorithm is utilized to determine possible paths from and to the node of the contamination detection. Considering the flow directions and patterns over time, the depth-first search (DFS) is used to explore the fate of the contaminant downstream, exclude possible sources, and to place mobile sensor equipment. By computing sub-graphs and clusters, possible source locations are identified for placing multiple grab samplings in strategically optimized locations, so the source can be detected quickly, and parts of the network can be identified as non-contaminated or as endangered of having deteriorating water quality. By utilizing the physical, topological, and hydraulic properties of the water network, a methodology is developed which enables water utilities to react to contamination events while collecting more information on the fate of the contamination downstream and the state of the water network in real time.