↓ Skip to main content

Surface-Water Nutrient Conditions and Sources in the United States Pacific Northwest1

Overview of attention for article published in Journal of the American Water Resources Association, August 2011
Altmetric Badge

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
40 Dimensions

Readers on

mendeley
59 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
Surface-Water Nutrient Conditions and Sources in the United States Pacific Northwest1
Published in
Journal of the American Water Resources Association, August 2011
DOI 10.1111/j.1752-1688.2011.00580.x
Pubmed ID
Authors

Daniel R. Wise, Henry M. Johnson

Abstract

The SPAtially Referenced Regressions On Watershed attributes (SPARROW) model was used to perform an assessment of surface-water nutrient conditions and to identify important nutrient sources in watersheds of the Pacific Northwest region of the United States (U.S.) for the year 2002. Our models included variables representing nutrient sources as well as landscape characteristics that affect nutrient delivery to streams. Annual nutrient yields were higher in watersheds on the wetter, west side of the Cascade Range compared to watersheds on the drier, east side. High nutrient enrichment (relative to the U.S. Environmental Protection Agency's recommended nutrient criteria) was estimated in watersheds throughout the region. Forest land was generally the largest source of total nitrogen stream load and geologic material was generally the largest source of total phosphorus stream load generated within the 12,039 modeled watersheds. These results reflected the prevalence of these two natural sources and the low input from other nutrient sources across the region. However, the combined input from agriculture, point sources, and developed land, rather than natural nutrient sources, was responsible for most of the nutrient load discharged from many of the largest watersheds. Our results provided an understanding of the regional patterns in surface-water nutrient conditions and should be useful to environmental managers in future water-quality planning efforts.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
Philippines 1 2%
Unknown 55 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 25%
Student > Master 14 24%
Researcher 10 17%
Professor 6 10%
Other 4 7%
Other 5 8%
Unknown 5 8%
Readers by discipline Count As %
Environmental Science 30 51%
Engineering 8 14%
Earth and Planetary Sciences 6 10%
Agricultural and Biological Sciences 2 3%
Computer Science 2 3%
Other 6 10%
Unknown 5 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 September 2011.
All research outputs
#10,438,019
of 13,089,117 outputs
Outputs from Journal of the American Water Resources Association
#597
of 715 outputs
Outputs of similar age
#71,843
of 91,764 outputs
Outputs of similar age from Journal of the American Water Resources Association
#7
of 11 outputs
Altmetric has tracked 13,089,117 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 715 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
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 91,764 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.