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River Water‐Quality Concentration and Flux Estimation Can be Improved by Accounting for Serial Correlation Through an Autoregressive Model

Overview of attention for article published in Water Resources Research, November 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

twitter
9 tweeters

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
16 Mendeley
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Title
River Water‐Quality Concentration and Flux Estimation Can be Improved by Accounting for Serial Correlation Through an Autoregressive Model
Published in
Water Resources Research, November 2019
DOI 10.1029/2019wr025338
Authors

Qian Zhang, Robert M. Hirsch

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 31%
Student > Ph. D. Student 3 19%
Student > Master 3 19%
Professor 2 13%
Professor > Associate Professor 1 6%
Other 0 0%
Unknown 2 13%
Readers by discipline Count As %
Engineering 4 25%
Environmental Science 4 25%
Agricultural and Biological Sciences 1 6%
Earth and Planetary Sciences 1 6%
Veterinary Science and Veterinary Medicine 1 6%
Other 0 0%
Unknown 5 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 29 November 2019.
All research outputs
#3,572,541
of 18,730,585 outputs
Outputs from Water Resources Research
#792
of 4,380 outputs
Outputs of similar age
#107,010
of 413,683 outputs
Outputs of similar age from Water Resources Research
#29
of 119 outputs
Altmetric has tracked 18,730,585 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,380 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has done well, scoring higher than 81% 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 413,683 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.