↓ Skip to main content

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
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
36 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
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

Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

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.
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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 22%
Student > Ph. D. Student 6 17%
Student > Master 4 11%
Professor 2 6%
Unspecified 1 3%
Other 3 8%
Unknown 12 33%
Readers by discipline Count As %
Environmental Science 7 19%
Engineering 6 17%
Agricultural and Biological Sciences 2 6%
Business, Management and Accounting 1 3%
Unspecified 1 3%
Other 5 14%
Unknown 14 39%
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
#6,785,715
of 26,476,278 outputs
Outputs from Water Resources Research
#1,612
of 5,476 outputs
Outputs of similar age
#133,617
of 484,283 outputs
Outputs of similar age from Water Resources Research
#29
of 110 outputs
Altmetric has tracked 26,476,278 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 5,476 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one has gotten more attention than average, scoring higher than 70% 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 484,283 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 72% of its contemporaries.
We're also able to compare this research output to 110 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 73% of its contemporaries.