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Potential Stream Density in Mid-Atlantic U.S. Watersheds

Stream network density exerts a strong influence on ecohydrologic processes in watersheds, yet existing stream maps fail to capture most headwater streams and therefore underestimate stream density. Furthermore, discrepancies between mapped and actual stream length vary between watersheds, confoundi...

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Autores principales: Elmore, Andrew J., Julian, Jason P., Guinn, Steven M., Fitzpatrick, Matthew C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3758290/
https://www.ncbi.nlm.nih.gov/pubmed/24023704
http://dx.doi.org/10.1371/journal.pone.0074819
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author Elmore, Andrew J.
Julian, Jason P.
Guinn, Steven M.
Fitzpatrick, Matthew C.
author_facet Elmore, Andrew J.
Julian, Jason P.
Guinn, Steven M.
Fitzpatrick, Matthew C.
author_sort Elmore, Andrew J.
collection PubMed
description Stream network density exerts a strong influence on ecohydrologic processes in watersheds, yet existing stream maps fail to capture most headwater streams and therefore underestimate stream density. Furthermore, discrepancies between mapped and actual stream length vary between watersheds, confounding efforts to understand the impacts of land use on stream ecosystems. Here we report on research that predicts stream presence from coupled field observations of headwater stream channels and terrain variables that were calculated both locally and as an average across the watershed upstream of any location on the landscape. Our approach used maximum entropy modeling (MaxEnt), a robust method commonly implemented to model species distributions that requires information only on the presence of the entity of interest. In validation, the method correctly predicts the presence of 86% of all 10-m stream segments and errors are low (<1%) for catchments larger than 10 ha. We apply this model to the entire Potomac River watershed (37,800 km(2)) and several adjacent watersheds to map stream density and compare our results with the National Hydrography Dataset (NHD). We find that NHD underestimates stream density by up to 250%, with errors being greatest in the densely urbanized cities of Washington, DC and Baltimore, MD and in regions where the NHD has never been updated from its original, coarse-grain mapping. This work is the most ambitious attempt yet to map stream networks over a large region and will have lasting implications for modeling and conservation efforts.
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spelling pubmed-37582902013-09-10 Potential Stream Density in Mid-Atlantic U.S. Watersheds Elmore, Andrew J. Julian, Jason P. Guinn, Steven M. Fitzpatrick, Matthew C. PLoS One Research Article Stream network density exerts a strong influence on ecohydrologic processes in watersheds, yet existing stream maps fail to capture most headwater streams and therefore underestimate stream density. Furthermore, discrepancies between mapped and actual stream length vary between watersheds, confounding efforts to understand the impacts of land use on stream ecosystems. Here we report on research that predicts stream presence from coupled field observations of headwater stream channels and terrain variables that were calculated both locally and as an average across the watershed upstream of any location on the landscape. Our approach used maximum entropy modeling (MaxEnt), a robust method commonly implemented to model species distributions that requires information only on the presence of the entity of interest. In validation, the method correctly predicts the presence of 86% of all 10-m stream segments and errors are low (<1%) for catchments larger than 10 ha. We apply this model to the entire Potomac River watershed (37,800 km(2)) and several adjacent watersheds to map stream density and compare our results with the National Hydrography Dataset (NHD). We find that NHD underestimates stream density by up to 250%, with errors being greatest in the densely urbanized cities of Washington, DC and Baltimore, MD and in regions where the NHD has never been updated from its original, coarse-grain mapping. This work is the most ambitious attempt yet to map stream networks over a large region and will have lasting implications for modeling and conservation efforts. Public Library of Science 2013-08-30 /pmc/articles/PMC3758290/ /pubmed/24023704 http://dx.doi.org/10.1371/journal.pone.0074819 Text en © 2013 Elmore et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Elmore, Andrew J.
Julian, Jason P.
Guinn, Steven M.
Fitzpatrick, Matthew C.
Potential Stream Density in Mid-Atlantic U.S. Watersheds
title Potential Stream Density in Mid-Atlantic U.S. Watersheds
title_full Potential Stream Density in Mid-Atlantic U.S. Watersheds
title_fullStr Potential Stream Density in Mid-Atlantic U.S. Watersheds
title_full_unstemmed Potential Stream Density in Mid-Atlantic U.S. Watersheds
title_short Potential Stream Density in Mid-Atlantic U.S. Watersheds
title_sort potential stream density in mid-atlantic u.s. watersheds
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3758290/
https://www.ncbi.nlm.nih.gov/pubmed/24023704
http://dx.doi.org/10.1371/journal.pone.0074819
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