Evidence map›Paper›PMID 30078989›Full record

ArticleEnvironmental modelling & software : with environment data news2018

Capturing Microbial Sources Distributed in a Mixed-use Watershed within an Integrated Environmental Modeling Workflow.

Gene Whelan, Keewook Kim, Rajbir Parmar, Gerard F Laniak, Kurt Wolfe, Michael Galvin, Marirosa Molina, Yakov A Pachepsky, Paul Duda, Richard Zepp and 4 more

Abstract read
In one paragraph

Article in Environmental modelling & software : with environment data news, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Gene WhelanU.S. Environmental Protection Agency, Office of Research and Development, Athens, GA USA.
Keewook KimIdaho Falls Center for Higher Education, University of Idaho, Idaho Falls, ID USA (currently at Busan Development Institute, Busan, South Korea).
Rajbir ParmarU.S. Environmental Protection Agency, Office of Research and Development, Athens, GA USA.
Gerard F LaniakU.S. Environmental Protection Agency, Office of Research and Development, Athens, GA USA.
Kurt WolfeU.S. Environmental Protection Agency, Office of Research and Development, Athens, GA USA.
Michael GalvinU.S. Environmental Protection Agency, Office of Research and Development, Athens, GA USA.
Marirosa MolinaU.S. Environmental Protection Agency, Office of Research and Development, Athens, GA USA.
Yakov A PachepskyU.S. Department of Agriculture, Agricultural Research Service, Beltsville, MD USA.
Paul DudaAQUA TERRA Consultants, a Division of RESPEC, INC, Decatur, GA USA.
Richard ZeppU.S. Environmental Protection Agency, Office of Research and Development, Athens, GA USA.
Lourdes PrietoU.S. Environmental Protection Agency, Office of Research and Development, Athens, GA USA.
Julie L KinzelmanPublic Health Department, Racine, WI USA.
Gregory T KleinheinzDepartment of Engineering Technology, University of Wisconsin Oshkosh, Oshkosh, WI USA.
Mark A BorchardtU.S. Department of Agriculture, Agricultural Research Service, Marshfield, WI USA.

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Many watershed models simulate overland and instream microbial fate and transport, but few provide loading rates on land surfaces and point sources to the waterbody network. This paper describes the underlying equations for microbial loading rates associated with 1) land-applied manure on undeveloped areas from domestic animals; 2) direct shedding (excretion) on undeveloped lands by domestic animals and wildlife; 3) urban or engineered areas; and 4) point sources that directly discharge to streams from septic systems and shedding by domestic animals. A microbial source module, which houses these formulations, is part of a workflow containing multiple models and databases that form a loosely configured modeling infrastructure which supports watershed-scale microbial source-to-receptor modeling by focusing on animal- and human-impacted catchments. A hypothetical application - accessing, retrieving, and using real-world data - demonstrates how the infrastructure can automate many of the manual steps associated with a standard watershed assessment, culminating in calibrated flow and microbial densities at the watershed's pour point.

Indexed as

Integrated environmental modelingmanurepathogensQMRArisk assessmentwatershed modeling

Identifiers

PMID30078989
PMCPMC6069999

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.