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• W4281779361 abstract "Water distribution systems are critical infrastructure that deliver high quality drinking water to its consumers. Contamination events in water distribution systems (WDS) are emergencies that can cause distress in the population and require quick response from the responsible utility manager. While regular water quality parameters are monitored at water treatment facilities, it is still a challenge to monitor water quality in the WDS itself. Various models have been developed to explore the reactions and interactions of relevant stakeholders during a contamination event including agent-based modelling. Furthermore, recent research has shown that water demands have significantly changed during the COVID-19 pandemic, and these changes can affect the operation and management of water infrastructure. In this study, an agent-based modelling framework is developed to explore social dynamics and reactions of water consumers and a utility manager during a contamination event, while considering a pandemic demand scenario. Furthermore, innovative response and recovery methods to a contamination event are explored for rehabilitating the water network after a water quality deterioration. Graph theory algorithms are used to place mobile sensor equipment for surveying the water quality in specific network parts, and the distribution system is clustered by the status of endangerment. The Bayesian Belief Network (BBN) was developed using survey data around risk perceptions and social distancing behaviour that were collected during the COVID-19 pandemic. The agent-based model (ABM) was developed using output from the BBN and water use data that were collected during the COVID-19 pandemic. The ABM is coupled with hydraulic simulation of the water infrastructure to evaluate changes in hydraulic performance. The model can be used to explore long and short-term consequences of the pandemic on water distribution systems’ management, design, and operations; develop and optimize strategies of how to deal with changes in around water distribution systems due to the pandemic; and investigate how resilient water utilities can cope with additional catastrophic events such as a contamination of a water system during a global or local pandemic related shutdown." @default.
• W4281779361 created "2022-06-13" @default.
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• W4281779361 date "2022-06-02" @default.
• W4281779361 modified "2023-09-27" @default.
• W4281779361 title "A Socio-Technological Framework for Optimizing Water Utility Strategies and Resilience to Pandemic Changes and Contamination Events" @default.
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• W4281779361 doi "https://doi.org/10.1061/9780784484258.085" @default.
• W4281779361 hasPublicationYear "2022" @default.
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