An Agent-Based Model for Contamination Response in Water Distribution Systems during the COVID-19 Pandemic

Abstract

Contamination events in water distribution systems (WDS) are emergencies that cause public health crises and require fast response by the responsible utility manager. Various models have been developed to explore the reactions of relevant stakeholders during a contamination event, including agent-based modeling. As the COVID-19 pandemic has changed the daily habits of communities around the globe, consumer water demands have changed dramatically. In this study, an agent-based modeling framework is developed to explore social dynamics and reactions of water consumers and a utility manager to a contamination event, while considering regular and pandemic demand scenarios. Utility manager agents use graph theory algorithms to place mobile sensor equipment and divide the network in sections that are endangered of being contaminated or cleared again for water consumption. The status of respective network nodes is communicated to consumer agents in real time, and consumer agents adjust their water demands accordingly. This sociotechnological framework is presented using the overview, design, and details protocol. The results comprise comparisons of reactions and demand adjustments of consumers to a water event during normal and pandemic times, while exploring new methods to predict the fate of a contaminant plume in the WDS.