Evidence map›Paper›PMID 38478973›Full record

ArticleEnvironmental science & technology2024

Using Inundation Extents to Predict Microbial Contamination in Private Wells after Flooding Events.

Kyla R Drewry, C Nathan Jones, Wesley Hayes, R Edward Beighley, Qi Wang, Jacob Hochard, Wilson Mize, Jon Fowlkes, Chris Goforth, Kelsey J Pieper

Abstract read
In one paragraph

Article in Environmental science & technology, 2024. 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

10 authors.

Kyla R DrewryDepartment of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States.ORCID 0000-0002-5574-0044
C Nathan JonesDepartment of Biological Sciences, University of Alabama, Tuscaloosa, Alabama 35401, United States.
Wesley HayesDepartment of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States.
R Edward BeighleyDepartment of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States.
Qi WangDepartment of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States.
Jacob HochardHaub School of Environment and Natural Resources, University of Wyoming, Laramie, Wyoming 82072, United States.
Wilson MizeDivision of Public Health, North Carolina Department of Health and Human Services, Raleigh, North Carolina 27609, United States.
Jon FowlkesDivision of Public Health, North Carolina Department of Health and Human Services, Raleigh, North Carolina 27609, United States.
Chris GoforthState Laboratory of Public Health, North Carolina Department of Health and Human Services, Raleigh, North Carolina 27609, United States.
Kelsey J PieperDepartment of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States.ORCID 0000-0002-0273-6527

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disaster recovery poses unique challenges for residents reliant on private wells. Flooding events are drivers of microbial contamination in well water, but the relationship observed between flooding and contamination varies substantially. Here, we investigate the performance of different flood boundaries─the FEMA 100 year flood hazard boundary, height above nearest drainage-derived inundation extents, and satellite-derived extents from the Dartmouth Flood Observatory─in their ability to identify well water contamination following Hurricane Florence. Using these flood boundaries, we estimated about 2600 wells to 108,400 private wells may have been inundated─over 2 orders of magnitude difference based on boundary used. Using state-generated routine and post-Florence testing data, we observed that microbial contamination rates were 7.1-10.5 times higher within the three flood boundaries compared to routine conditions. However, the ability of the flood boundaries to identify contaminated samples varied spatially depending on the type of flooding (e.g., riverine, overbank, coastal). While participation in testing increased after Florence, rates were overall still low. With <1% of wells tested, there is a critical need for enhanced well water testing efforts. This work provides an understanding of the strengths and limitations of inundation mapping techniques, which are critical for guiding postdisaster well water response and recovery.

Indexed as

Cyclonic StormsFloodsWaterWater PollutionWaterflood boundariesinundation mappingmicrobial contaminationprivate wellswell water

Identifiers

PMID38478973
PMCPMC10976889

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.