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Sediment source fingerprinting as an aid to catchment management: A review of the current state of knowledge and a methodological decision-tree for end-users

Overview of attention for article published in Journal of Environmental Management, October 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
7 X users

Citations

dimensions_citation
209 Dimensions

Readers on

mendeley
284 Mendeley
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Title
Sediment source fingerprinting as an aid to catchment management: A review of the current state of knowledge and a methodological decision-tree for end-users
Published in
Journal of Environmental Management, October 2016
DOI 10.1016/j.jenvman.2016.09.075
Pubmed ID
Authors

A.L. Collins, S. Pulley, I.D.L. Foster, A. Gellis, P. Porto, A.J. Horowitz

Abstract

The growing awareness of the environmental significance of fine-grained sediment fluxes through catchment systems continues to underscore the need for reliable information on the principal sources of this material. Source estimates are difficult to obtain using traditional monitoring techniques, but sediment source fingerprinting or tracing procedures, have emerged as a potentially valuable alternative. Despite the rapidly increasing numbers of studies reporting the use of sediment source fingerprinting, several key challenges and uncertainties continue to hamper consensus among the international scientific community on key components of the existing methodological procedures. Accordingly, this contribution reviews and presents recent developments for several key aspects of fingerprinting, namely: sediment source classification, catchment source and target sediment sampling, tracer selection, grain size issues, tracer conservatism, source apportionment modelling, and assessment of source predictions using artificial mixtures. Finally, a decision-tree representing the current state of knowledge is presented, to guide end-users in applying the fingerprinting approach.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 284 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 1 <1%
Unknown 283 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 50 18%
Student > Master 46 16%
Researcher 36 13%
Student > Bachelor 19 7%
Student > Doctoral Student 15 5%
Other 35 12%
Unknown 83 29%
Readers by discipline Count As %
Environmental Science 69 24%
Earth and Planetary Sciences 49 17%
Engineering 18 6%
Agricultural and Biological Sciences 15 5%
Computer Science 5 2%
Other 18 6%
Unknown 110 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 October 2022.
All research outputs
#2,575,341
of 25,374,647 outputs
Outputs from Journal of Environmental Management
#526
of 6,438 outputs
Outputs of similar age
#42,850
of 326,114 outputs
Outputs of similar age from Journal of Environmental Management
#10
of 107 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,438 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,114 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.