Agent-Based Modeling to Simulate Contamination Events and to Analyze Threat Management Strategies in Water Distribution Systems

In the event of contamination of a water distribution system, decisions must be made to mitigate the impact of the contamination to protect public health. Making threat management decisions while the contaminant is spreading through the network is a difficult process due to uncertainty and lack of monitoring data. This is further complicated by the response actions taken by the utility managers and water consumption choices made by the consumers as they all will affect the hydraulics, thus the spread of the contaminant plume, in the network. A modeling framework that allows the simulation of a contamination event under the effects of actions taken by utility managers and consumers will be a useful tool for the analysis of alternative threat mitigation and management strategies. The complex interactions between the managers' network operation decisions and consumers' water consumption choices, and the response of the hydraulics and contaminant transport in the water distribution system will be simulated using an agent-based modeling approach. Agent-based models are simulated individuals that are formulated as interacting autonomous entities. Each agent selects actions based on a set of rules that represent an individual's autonomy, goal-based desires, and reaction to the environment and the actions of other agents. This paper presents a multi-agent modeling framework that will combine agent-based, mechanistic, and dynamic methods. As actions taken by agents affect demands and flows in the system, dynamic approaches will update the mechanistic model and the identification of the contaminant source to supply the "utility manager" agents with the latest information as it becomes available. The framework will be designed to consider the typical issues involved in water distribution threat management and will provide valuable analysis of threat containment strategies for water distribution system contamination events.