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Predicting nonpoint stormwater runoff quality from land use
Evaluating the impact of urban development on natural ecosystem processes has become an increasingly complex task for planners, environmental scientists, and engineers. As the built environment continues to grow, unregulated nonpoint pollutants from increased human activity and large-scale developme...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5942771/ https://www.ncbi.nlm.nih.gov/pubmed/29742172 http://dx.doi.org/10.1371/journal.pone.0196782 |
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author | Zivkovich, Brik R. Mays, David C. |
author_facet | Zivkovich, Brik R. Mays, David C. |
author_sort | Zivkovich, Brik R. |
collection | PubMed |
description | Evaluating the impact of urban development on natural ecosystem processes has become an increasingly complex task for planners, environmental scientists, and engineers. As the built environment continues to grow, unregulated nonpoint pollutants from increased human activity and large-scale development severely stress urban streams and lakes resulting in their currently impaired or degraded state. In response, integrated water quality management programs have been adopted to address these unregulated nonpoint pollutants by utilizing best management practices (BMPs) that treat runoff as close to the source as possible. Knowing where to install effective BMPs is no trivial task, considering budget constraints and the spatially extensive nature of nonpoint stormwater runoff. Accordingly, this paper presents an initial, straightforward and cost-effective methodology to identify critical nonpoint pollutant source watersheds through correlation of water quality with land use. Through an illustrative application to metropolitan Denver, Colorado, it is shown how this method can be used to aid stormwater professionals to evaluate and specify retrofit locations in need of water quality treatment features reduce, capture and treat stormwater runoff prior to entering receiving waters. |
format | Online Article Text |
id | pubmed-5942771 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-59427712018-05-18 Predicting nonpoint stormwater runoff quality from land use Zivkovich, Brik R. Mays, David C. PLoS One Research Article Evaluating the impact of urban development on natural ecosystem processes has become an increasingly complex task for planners, environmental scientists, and engineers. As the built environment continues to grow, unregulated nonpoint pollutants from increased human activity and large-scale development severely stress urban streams and lakes resulting in their currently impaired or degraded state. In response, integrated water quality management programs have been adopted to address these unregulated nonpoint pollutants by utilizing best management practices (BMPs) that treat runoff as close to the source as possible. Knowing where to install effective BMPs is no trivial task, considering budget constraints and the spatially extensive nature of nonpoint stormwater runoff. Accordingly, this paper presents an initial, straightforward and cost-effective methodology to identify critical nonpoint pollutant source watersheds through correlation of water quality with land use. Through an illustrative application to metropolitan Denver, Colorado, it is shown how this method can be used to aid stormwater professionals to evaluate and specify retrofit locations in need of water quality treatment features reduce, capture and treat stormwater runoff prior to entering receiving waters. Public Library of Science 2018-05-09 /pmc/articles/PMC5942771/ /pubmed/29742172 http://dx.doi.org/10.1371/journal.pone.0196782 Text en © 2018 Zivkovich, Mays http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Zivkovich, Brik R. Mays, David C. Predicting nonpoint stormwater runoff quality from land use |
title | Predicting nonpoint stormwater runoff quality from land use |
title_full | Predicting nonpoint stormwater runoff quality from land use |
title_fullStr | Predicting nonpoint stormwater runoff quality from land use |
title_full_unstemmed | Predicting nonpoint stormwater runoff quality from land use |
title_short | Predicting nonpoint stormwater runoff quality from land use |
title_sort | predicting nonpoint stormwater runoff quality from land use |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5942771/ https://www.ncbi.nlm.nih.gov/pubmed/29742172 http://dx.doi.org/10.1371/journal.pone.0196782 |
work_keys_str_mv | AT zivkovichbrikr predictingnonpointstormwaterrunoffqualityfromlanduse AT maysdavidc predictingnonpointstormwaterrunoffqualityfromlanduse |