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Impacts of COVID-19 social distancing policies on water demand: A population dynamics perspective
Social distancing policies (SDPs) implemented in response to the COVID-19 pandemic have led to temporal and spatial shifts in water demand across cities. Water utilities need to understand these demand shifts to respond to potential operational and water-quality issues. Aided by a fixed-effects mode...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519786/ https://www.ncbi.nlm.nih.gov/pubmed/34872171 http://dx.doi.org/10.1016/j.jenvman.2021.113949 |
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author | Bakchan, Amal Roy, Arkajyoti Faust, Kasey M. |
author_facet | Bakchan, Amal Roy, Arkajyoti Faust, Kasey M. |
author_sort | Bakchan, Amal |
collection | PubMed |
description | Social distancing policies (SDPs) implemented in response to the COVID-19 pandemic have led to temporal and spatial shifts in water demand across cities. Water utilities need to understand these demand shifts to respond to potential operational and water-quality issues. Aided by a fixed-effects model of citywide water demand in Austin, Texas, we explore the impacts of various SDPs (e.g., time after the stay home-work safe order, reopening phases) using daily demand data gathered between 2013 and 2020. Our approach uses socio-technical determinants (e.g., climate, water conservation policy) with SDPs to model water demand, while accounting for spatial and temporal effects (e.g., geographic variations, weekday patterns). Results indicate shifts in behavior of residential and nonresidential demands that offset the change at the system scale, demonstrating a spatial redistribution of water demand after the stay home-work safe order. Our results show that some phases of Texas's reopening phases had statistically significant relationships to water demand. While this yielded only marginal net effects on overall demand, it underscores behavioral changes in demand at sub-system spatial scales. Our discussions shed light on SDPs' impacts on water demand. Equipped with our empirical findings, utilities can respond to potential vulnerabilities in their systems, such as water-quality problems that may be related to changes in water pressure in response to demand variations. |
format | Online Article Text |
id | pubmed-8519786 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85197862021-10-18 Impacts of COVID-19 social distancing policies on water demand: A population dynamics perspective Bakchan, Amal Roy, Arkajyoti Faust, Kasey M. J Environ Manage Article Social distancing policies (SDPs) implemented in response to the COVID-19 pandemic have led to temporal and spatial shifts in water demand across cities. Water utilities need to understand these demand shifts to respond to potential operational and water-quality issues. Aided by a fixed-effects model of citywide water demand in Austin, Texas, we explore the impacts of various SDPs (e.g., time after the stay home-work safe order, reopening phases) using daily demand data gathered between 2013 and 2020. Our approach uses socio-technical determinants (e.g., climate, water conservation policy) with SDPs to model water demand, while accounting for spatial and temporal effects (e.g., geographic variations, weekday patterns). Results indicate shifts in behavior of residential and nonresidential demands that offset the change at the system scale, demonstrating a spatial redistribution of water demand after the stay home-work safe order. Our results show that some phases of Texas's reopening phases had statistically significant relationships to water demand. While this yielded only marginal net effects on overall demand, it underscores behavioral changes in demand at sub-system spatial scales. Our discussions shed light on SDPs' impacts on water demand. Equipped with our empirical findings, utilities can respond to potential vulnerabilities in their systems, such as water-quality problems that may be related to changes in water pressure in response to demand variations. Elsevier Ltd. 2022-01-15 2021-10-16 /pmc/articles/PMC8519786/ /pubmed/34872171 http://dx.doi.org/10.1016/j.jenvman.2021.113949 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Bakchan, Amal Roy, Arkajyoti Faust, Kasey M. Impacts of COVID-19 social distancing policies on water demand: A population dynamics perspective |
title | Impacts of COVID-19 social distancing policies on water demand: A population dynamics perspective |
title_full | Impacts of COVID-19 social distancing policies on water demand: A population dynamics perspective |
title_fullStr | Impacts of COVID-19 social distancing policies on water demand: A population dynamics perspective |
title_full_unstemmed | Impacts of COVID-19 social distancing policies on water demand: A population dynamics perspective |
title_short | Impacts of COVID-19 social distancing policies on water demand: A population dynamics perspective |
title_sort | impacts of covid-19 social distancing policies on water demand: a population dynamics perspective |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519786/ https://www.ncbi.nlm.nih.gov/pubmed/34872171 http://dx.doi.org/10.1016/j.jenvman.2021.113949 |
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