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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 (74th percentile)

Mentioned by

twitter
8 X users

Citations

dimensions_citation
35 Dimensions

Readers on

mendeley
35 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

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 23%
Student > Ph. D. Student 6 17%
Student > Master 4 11%
Professor 2 6%
Student > Doctoral Student 1 3%
Other 2 6%
Unknown 12 34%
Readers by discipline Count As %
Environmental Science 7 20%
Engineering 6 17%
Agricultural and Biological Sciences 2 6%
Business, Management and Accounting 1 3%
Unspecified 1 3%
Other 5 14%
Unknown 13 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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
#5,514,286
of 23,177,498 outputs
Outputs from Water Resources Research
#1,287
of 4,923 outputs
Outputs of similar age
#115,061
of 458,595 outputs
Outputs of similar age from Water Resources Research
#28
of 109 outputs
Altmetric has tracked 23,177,498 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,923 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has gotten more attention than average, scoring higher than 73% 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 458,595 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 109 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.