In the event that a contaminant is introduced to a water distribution network, a large population of consumers may risk exposure. Selecting mitigation actions to protect public health may be difficult, as contamination is a poorly predictable dynamic event. Consumers who become aware of an event may select protective actions to change their water demands from typical demand patterns, and new hydraulic conditions can arise that differ from conditions that would be predicted when demands are considered as exogenous inputs. Consequently, the movement of the contaminant plume in the pipe network may shift from its expected trajectory. A sociotechnical model is developed here to integrate agent-based models of consumers with an engineering water distribution system model and capture the dynamics between consumer behaviors and the water distribution system for predicting contaminant transport and public exposure. Consumers are simulated as agents with behaviors, including movement, water consumption, exposure, reduction in demands, and communication with other agents. As consumers decrease their water use, the location of the contaminant plume is updated and the amount of contaminant consumed by each agent is calculated. The framework is tested through simulating realistic contamination scenarios for a virtual city and water distribution system.
Cascading effects of cyber-attacks on interconnected critical infrastructure
