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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 (89th percentile)

Mentioned by

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

Citations

dimensions_citation
56 Dimensions

Readers on

mendeley
83 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 2 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 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
Spain 1 1%
Unknown 79 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 24%
Student > Master 20 24%
Researcher 18 22%
Other 6 7%
Professor > Associate Professor 5 6%
Other 9 11%
Unknown 5 6%
Readers by discipline Count As %
Environmental Science 35 42%
Earth and Planetary Sciences 14 17%
Engineering 11 13%
Agricultural and Biological Sciences 6 7%
Medicine and Dentistry 2 2%
Other 2 2%
Unknown 13 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 24 November 2013.
All research outputs
#232,517
of 4,507,509 outputs
Outputs from Environmental Science & Technology
#481
of 4,705 outputs
Outputs of similar age
#7,973
of 102,749 outputs
Outputs of similar age from Environmental Science & Technology
#27
of 259 outputs
Altmetric has tracked 4,507,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,705 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done well, scoring higher than 89% 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 102,749 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 259 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.