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Using Wastewater Flow to Understand Water System’s Demand Behavior during the COVID-19 Pandemic in an Urban Metropolitan City in Texas
Social distancing policies (SDPs) implemented in response to the COVID-19 pandemic have led to spatiotemporal variations in water demand. In contexts with limited availability of smart meter infrastructure, the lack of high-granular water demand data challenges utilities’ understanding of such demand variations that are needed to respond to potential operational and water quality issues. Founded on the water and wastewater infrastructure’s interdependencies, this study proposes the use of high-granular wastewater flow data as a proxy to understand the water demand variations during active SDPs. Enabled by a random-effects model of wastewater flow in an urban metropolitan city in Texas, we explore the impacts of various SDPs (e.g., stay home-work safe, reopening phases) using daily flow data gathered between March 19, 2019, and December 31, 2020. Results indicate an increase in residential flow that offset a decrease in nonresidential flow during the stay home-work safe period. Our results also show that the three reopening phases have statistically significant relationships to wastewater flow, although yielding marginal net effects at the system scale. These findings in regard to residential–nonresidential variations—explored through the wastewater flow—underscore behavioral changes in water demand at sub-system spatial scales. Our assessment can inform emergency response plans for pandemics in regard to water infrastructure planning, management, and operations, considering spatiotemporal changes in water demand.
Using Wastewater Flow to Understand Water System’s Demand Behavior during the COVID-19 Pandemic in an Urban Metropolitan City in Texas
Social distancing policies (SDPs) implemented in response to the COVID-19 pandemic have led to spatiotemporal variations in water demand. In contexts with limited availability of smart meter infrastructure, the lack of high-granular water demand data challenges utilities’ understanding of such demand variations that are needed to respond to potential operational and water quality issues. Founded on the water and wastewater infrastructure’s interdependencies, this study proposes the use of high-granular wastewater flow data as a proxy to understand the water demand variations during active SDPs. Enabled by a random-effects model of wastewater flow in an urban metropolitan city in Texas, we explore the impacts of various SDPs (e.g., stay home-work safe, reopening phases) using daily flow data gathered between March 19, 2019, and December 31, 2020. Results indicate an increase in residential flow that offset a decrease in nonresidential flow during the stay home-work safe period. Our results also show that the three reopening phases have statistically significant relationships to wastewater flow, although yielding marginal net effects at the system scale. These findings in regard to residential–nonresidential variations—explored through the wastewater flow—underscore behavioral changes in water demand at sub-system spatial scales. Our assessment can inform emergency response plans for pandemics in regard to water infrastructure planning, management, and operations, considering spatiotemporal changes in water demand.
Using Wastewater Flow to Understand Water System’s Demand Behavior during the COVID-19 Pandemic in an Urban Metropolitan City in Texas
Bakchan, Amal (Autor:in) / Roy, Arkajyoti (Autor:in) / Faust, Kasey M. (Autor:in)
Construction Research Congress 2022 ; 2022 ; Arlington, Virginia
Construction Research Congress 2022 ; 427-436
07.03.2022
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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