Estimating fluvial wood discharge using time‐lapse photography with varying sampling intervals

ABSTRACT Monitoring large wood (LW: width > 10 cm, length > 1 m) in transport within rivers is a necessary next step in the development and refinement of wood budgets and is essential to a better understanding of basin‐wide controls and patterns of LW flux and loads. Monitoring LW transport wi...

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Published in:Earth Surface Processes and Landforms
Main Authors: Kramer, Natalie, Wohl, Ellen
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2014
Subjects:
Online Access:http://dx.doi.org/10.1002/esp.3540
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fesp.3540
https://onlinelibrary.wiley.com/doi/pdf/10.1002/esp.3540
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spelling crwiley:10.1002/esp.3540 2024-06-23T07:56:45+00:00 Estimating fluvial wood discharge using time‐lapse photography with varying sampling intervals Kramer, Natalie Wohl, Ellen 2014 http://dx.doi.org/10.1002/esp.3540 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fesp.3540 https://onlinelibrary.wiley.com/doi/pdf/10.1002/esp.3540 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Earth Surface Processes and Landforms volume 39, issue 6, page 844-852 ISSN 0197-9337 1096-9837 journal-article 2014 crwiley https://doi.org/10.1002/esp.3540 2024-06-13T04:23:48Z ABSTRACT Monitoring large wood (LW: width > 10 cm, length > 1 m) in transport within rivers is a necessary next step in the development and refinement of wood budgets and is essential to a better understanding of basin‐wide controls and patterns of LW flux and loads. Monitoring LW transport with coarse interval (≥ 1 min) time‐lapse photography enables the deployment of monitoring cameras at large spatial and long temporal scales. Although less precise than continuous sampling with video, it allows investigators to answer broad questions about basin connectivity, compare drainages and years,and identify transport relationships and thresholds. This paper describes methods to: (i) construct fluvial wood flux curves; (ii) analyze the effects of sample interval lengths on transport estimates; and (iii) estimate total wood loads within a specified time period using coarse‐interval time‐lapse photography. Applying these methods to the Slave River, a large‐volume (10 3 m 3 s ‐1 ), low‐gradient (10 − 2 m km − 1 ) river in the subarctic (60 ∘ N), yielded the following results. A threshold relationship for wood mobility was located around 4500 m 3 s ‐1 . More wood is transported on the rising limb of the hydrograph because wood flux declines rapidly on the falling limb. Five‐ and ten‐minute sampling intervals provided unbiased equal variance estimates of 1 min sampling, whereas 15 min intervals were biased towards underestimation by 5–6%, possibly due to periodicity in wood flux. Total LW loads estimated from the 1 min dataset and adjusted for a 15% misdetection rate from 13 July to 13 August are: 1600 ± 200 # pieces, 600 ± 200 m 3 and of the order of 1.3 × 10 5 kg carbon. The total wood load for the entire summer season is probably at least double this estimate because only the second half of the summer was monitored and a large early summer peak freshet was missed. Copyright © 2014 John Wiley & Sons, Ltd. Article in Journal/Newspaper Slave River Subarctic Wiley Online Library Earth Surface Processes and Landforms 39 6 844 852
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language English
description ABSTRACT Monitoring large wood (LW: width > 10 cm, length > 1 m) in transport within rivers is a necessary next step in the development and refinement of wood budgets and is essential to a better understanding of basin‐wide controls and patterns of LW flux and loads. Monitoring LW transport with coarse interval (≥ 1 min) time‐lapse photography enables the deployment of monitoring cameras at large spatial and long temporal scales. Although less precise than continuous sampling with video, it allows investigators to answer broad questions about basin connectivity, compare drainages and years,and identify transport relationships and thresholds. This paper describes methods to: (i) construct fluvial wood flux curves; (ii) analyze the effects of sample interval lengths on transport estimates; and (iii) estimate total wood loads within a specified time period using coarse‐interval time‐lapse photography. Applying these methods to the Slave River, a large‐volume (10 3 m 3 s ‐1 ), low‐gradient (10 − 2 m km − 1 ) river in the subarctic (60 ∘ N), yielded the following results. A threshold relationship for wood mobility was located around 4500 m 3 s ‐1 . More wood is transported on the rising limb of the hydrograph because wood flux declines rapidly on the falling limb. Five‐ and ten‐minute sampling intervals provided unbiased equal variance estimates of 1 min sampling, whereas 15 min intervals were biased towards underestimation by 5–6%, possibly due to periodicity in wood flux. Total LW loads estimated from the 1 min dataset and adjusted for a 15% misdetection rate from 13 July to 13 August are: 1600 ± 200 # pieces, 600 ± 200 m 3 and of the order of 1.3 × 10 5 kg carbon. The total wood load for the entire summer season is probably at least double this estimate because only the second half of the summer was monitored and a large early summer peak freshet was missed. Copyright © 2014 John Wiley & Sons, Ltd.
format Article in Journal/Newspaper
author Kramer, Natalie
Wohl, Ellen
spellingShingle Kramer, Natalie
Wohl, Ellen
Estimating fluvial wood discharge using time‐lapse photography with varying sampling intervals
author_facet Kramer, Natalie
Wohl, Ellen
author_sort Kramer, Natalie
title Estimating fluvial wood discharge using time‐lapse photography with varying sampling intervals
title_short Estimating fluvial wood discharge using time‐lapse photography with varying sampling intervals
title_full Estimating fluvial wood discharge using time‐lapse photography with varying sampling intervals
title_fullStr Estimating fluvial wood discharge using time‐lapse photography with varying sampling intervals
title_full_unstemmed Estimating fluvial wood discharge using time‐lapse photography with varying sampling intervals
title_sort estimating fluvial wood discharge using time‐lapse photography with varying sampling intervals
publisher Wiley
publishDate 2014
url http://dx.doi.org/10.1002/esp.3540
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fesp.3540
https://onlinelibrary.wiley.com/doi/pdf/10.1002/esp.3540
genre Slave River
Subarctic
genre_facet Slave River
Subarctic
op_source Earth Surface Processes and Landforms
volume 39, issue 6, page 844-852
ISSN 0197-9337 1096-9837
op_rights http://onlinelibrary.wiley.com/termsAndConditions#vor
op_doi https://doi.org/10.1002/esp.3540
container_title Earth Surface Processes and Landforms
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container_issue 6
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