Leveraging water-wastewater data interdependencies to understand infrastructure systems' behaviors during COVID-19 pandemic.

ABSTRACT: Social distancing policies (SDPs) implemented worldwide in response to COVID-19 pandemic have led to spatiotemporal variations in water demand and wastewater flow, creating potential operational and service-related quality issues in water-sector infrastructure. Understanding water-demand variations is especially challenging in contexts with limited availability of smart meter infrastructure, hindering utilities' ability to respond in real time to identified system vulnerabilities. Leveraging water and wastewater infrastructures' interdependencies, this study proposes the use of high-granular wastewater-flow data as a proxy to understand both water and wastewater systems' behaviors during active SDPs. Enabled by a random-effects model of wastewater flow in an urban metropolitan city in Texa

SUBMITTER: Bakchan A 

PROVIDER: S-EPMC9249819 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature