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Quantifying Groundwater’s Role in Delaying Improvements to Chesapeake Bay Water Quality

Overview of attention for article published in Environmental Science & Technology, November 2013
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
6 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
78 Dimensions

Readers on

mendeley
111 Mendeley
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Title
Quantifying Groundwater’s Role in Delaying Improvements to Chesapeake Bay Water Quality
Published in
Environmental Science & Technology, November 2013
DOI 10.1021/es401334k
Pubmed ID
Authors

Ward E. Sanford, Jason P. Pope

Abstract

A study has been undertaken to determine the time required for the effects of nitrogen-reducing best management practices (BMPs) implemented at the land surface to reach the Chesapeake Bay via groundwater transport to streams. To accomplish this, a nitrogen mass-balance regression (NMBR) model was developed and applied to seven watersheds on the Delmarva Peninsula. The model included the distribution of groundwater return times obtained from a regional groundwater-flow (GWF) model, the history of nitrogen application at the land surface over the last century, and parameters that account for denitrification. The model was (1) able to reproduce nitrate concentrations in streams and wells over time, including a recent decline in the rate at which concentrations have been increasing, and (2) used to forecast future nitrogen delivery from the Delmarva Peninsula to the Bay given different scenarios of nitrogen load reduction to the water table. The relatively deep porous aquifers of the Delmarva yield longer groundwater return times than those reported earlier for western parts of the Bay watershed. Accordingly, several decades will be required to see the full effects of current and future BMPs. The magnitude of this time lag is critical information for Chesapeake Bay watershed managers and stakeholders.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Unknown 109 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 23%
Student > Ph. D. Student 24 22%
Student > Master 23 21%
Student > Bachelor 6 5%
Professor > Associate Professor 6 5%
Other 14 13%
Unknown 13 12%
Readers by discipline Count As %
Environmental Science 38 34%
Engineering 16 14%
Earth and Planetary Sciences 16 14%
Agricultural and Biological Sciences 8 7%
Medicine and Dentistry 4 4%
Other 5 5%
Unknown 24 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 14 April 2021.
All research outputs
#1,270,503
of 18,247,290 outputs
Outputs from Environmental Science & Technology
#1,702
of 17,413 outputs
Outputs of similar age
#14,966
of 197,581 outputs
Outputs of similar age from Environmental Science & Technology
#30
of 254 outputs
Altmetric has tracked 18,247,290 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,413 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one has done particularly well, scoring higher than 90% 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 197,581 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 254 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.