Predicting maximum lake depth from surrounding topography.

Information about lake morphometry (e.g., depth, volume, size, etc.) aids understanding of the physical and ecological dynamics of lakes, yet is often not readily available. The data needed to calculate measures of lake morphometry, particularly lake depth, are usually collected on a lake-by-lake ba...

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Main Authors: Jeffrey W Hollister, W Bryan Milstead, M Andrea Urrutia
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3184154?pdf=render
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spelling doaj-344a6d68bc4f4ee298267b397078d6a82020-11-25T02:27:38ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-01-0169e2576410.1371/journal.pone.0025764Predicting maximum lake depth from surrounding topography.Jeffrey W HollisterW Bryan MilsteadM Andrea UrrutiaInformation about lake morphometry (e.g., depth, volume, size, etc.) aids understanding of the physical and ecological dynamics of lakes, yet is often not readily available. The data needed to calculate measures of lake morphometry, particularly lake depth, are usually collected on a lake-by-lake basis and are difficult to obtain across broad regions. To span the gap between studies of individual lakes where detailed data exist and regional studies where access to useful data on lake depth is unavailable, we developed a method to predict maximum lake depth from the slope of the topography surrounding a lake. We use the National Elevation Dataset and the National Hydrography Dataset - Plus to estimate the percent slope of surrounding lakes and use this information to predict maximum lake depth. We also use field measured maximum lake depths from the US EPA's National Lakes Assessment to empirically adjust and cross-validate our predictions. We were able to predict maximum depth for ∼28,000 lakes in the Northeastern United States with an average cross-validated RMSE of 5.95 m and 5.09 m and average correlation of 0.82 and 0.69 for Hydrological Unit Code Regions 01 and 02, respectively. The depth predictions and the scripts are openly available as supplements to this manuscript.http://europepmc.org/articles/PMC3184154?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Jeffrey W Hollister
W Bryan Milstead
M Andrea Urrutia
spellingShingle Jeffrey W Hollister
W Bryan Milstead
M Andrea Urrutia
Predicting maximum lake depth from surrounding topography.
PLoS ONE
author_facet Jeffrey W Hollister
W Bryan Milstead
M Andrea Urrutia
author_sort Jeffrey W Hollister
title Predicting maximum lake depth from surrounding topography.
title_short Predicting maximum lake depth from surrounding topography.
title_full Predicting maximum lake depth from surrounding topography.
title_fullStr Predicting maximum lake depth from surrounding topography.
title_full_unstemmed Predicting maximum lake depth from surrounding topography.
title_sort predicting maximum lake depth from surrounding topography.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2011-01-01
description Information about lake morphometry (e.g., depth, volume, size, etc.) aids understanding of the physical and ecological dynamics of lakes, yet is often not readily available. The data needed to calculate measures of lake morphometry, particularly lake depth, are usually collected on a lake-by-lake basis and are difficult to obtain across broad regions. To span the gap between studies of individual lakes where detailed data exist and regional studies where access to useful data on lake depth is unavailable, we developed a method to predict maximum lake depth from the slope of the topography surrounding a lake. We use the National Elevation Dataset and the National Hydrography Dataset - Plus to estimate the percent slope of surrounding lakes and use this information to predict maximum lake depth. We also use field measured maximum lake depths from the US EPA's National Lakes Assessment to empirically adjust and cross-validate our predictions. We were able to predict maximum depth for ∼28,000 lakes in the Northeastern United States with an average cross-validated RMSE of 5.95 m and 5.09 m and average correlation of 0.82 and 0.69 for Hydrological Unit Code Regions 01 and 02, respectively. The depth predictions and the scripts are openly available as supplements to this manuscript.
url http://europepmc.org/articles/PMC3184154?pdf=render
work_keys_str_mv AT jeffreywhollister predictingmaximumlakedepthfromsurroundingtopography
AT wbryanmilstead predictingmaximumlakedepthfromsurroundingtopography
AT mandreaurrutia predictingmaximumlakedepthfromsurroundingtopography
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