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An overview of current applications, challenges, and future trends in distributed process-based models in hydrology

Overview of attention for article published in Journal of Hydrology, June 2016
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  • Average Attention Score compared to outputs of the same age
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

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4 X users

Citations

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368 Dimensions

Readers on

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745 Mendeley
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Title
An overview of current applications, challenges, and future trends in distributed process-based models in hydrology
Published in
Journal of Hydrology, June 2016
DOI 10.1016/j.jhydrol.2016.03.026
Authors

Simone Fatichi, Enrique R. Vivoni, Fred L. Ogden, Valeriy Y. Ivanov, Benjamin Mirus, David Gochis, Charles W. Downer, Matteo Camporese, Jason H. Davison, Brian Ebel, Norm Jones, Jongho Kim, Giuseppe Mascaro, Richard Niswonger, Pedro Restrepo, Riccardo Rigon, Chaopeng Shen, Mauro Sulis, David Tarboton

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 745 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
Canada 2 <1%
Belgium 2 <1%
Chile 1 <1%
Unknown 738 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 207 28%
Researcher 103 14%
Student > Master 95 13%
Student > Doctoral Student 61 8%
Professor > Associate Professor 30 4%
Other 103 14%
Unknown 146 20%
Readers by discipline Count As %
Engineering 170 23%
Environmental Science 150 20%
Earth and Planetary Sciences 146 20%
Agricultural and Biological Sciences 29 4%
Computer Science 11 1%
Other 41 6%
Unknown 198 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 January 2020.
All research outputs
#14,536,007
of 25,373,627 outputs
Outputs from Journal of Hydrology
#2,573
of 8,696 outputs
Outputs of similar age
#178,946
of 353,659 outputs
Outputs of similar age from Journal of Hydrology
#13
of 105 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,696 research outputs from this source. They receive a mean Attention Score of 3.2. 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 353,659 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 105 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.