Evidence map›Paper›PMID 34951307›Full record

ArticleEnvironmental science & technology2022

Surface Flooding as a Key Driver of Groundwater Arsenic Contamination in Southeast Asia.

Craig T Connolly, Mason O Stahl, Beck A DeYoung, Benjamin C Bostick

Abstract read
In one paragraph

Article in Environmental science & technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

4 authors.

Craig T ConnollyLamont-Doherty Earth Observatory, Columbia University, 61 Route 9W, Palisades, New York 10964, United States.ORCID 0000-0002-6090-3215
Mason O StahlDepartment of Geology, Union College, 807 Union Street, Schenectady, New York 12308, United States.
Beck A DeYoungDepartment of Geology, Union College, 807 Union Street, Schenectady, New York 12308, United States.ORCID 0000-0002-5340-3394
Benjamin C BostickLamont-Doherty Earth Observatory, Columbia University, 61 Route 9W, Palisades, New York 10964, United States.ORCID 0000-0002-7513-6469

Funding

Training CoreP42ES010349 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI NAVAS-ACIEN, ANA · 2000 to 2020
$53.6M
Supplemental Training in Making Data FAIR and AI/ML ReadyT32ES007322 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Pam R Factor-Litvak, Allison Kupsco · 2000 to 2026
$12.1M
NIEHS NIH HHS P42 ES010349NIEHS NIH HHS T32 ES007322
6 · The paper itself

Abstract

Chronic exposure to groundwater contaminated with geogenic arsenic (As) poses a significant threat to human health worldwide, especially for those living on floodplains in South and Southeast (S-SE) Asia. In the alluvial and deltaic aquifers of S-SE Asia, aqueous As concentrations vary sharply over small spatial scales (10-100 m), making it challenging to identify where As contamination is present and mitigate exposure. Improved mechanistic understanding of the factors that control groundwater As levels is essential to develop models that accurately predict spatially variable groundwater As concentrations. Here we demonstrate that surface flooding duration and interannual frequency are master variables that integrate key hydrologic and biogeochemical processes that affect groundwater As levels in S-SE Asia. A machine-learning model based on high-resolution, satellite-derived, long-term measures of surface flooding duration and frequency effectively predicts heterogeneous groundwater As concentrations at fine spatial scales in Cambodia, Vietnam, and Bangladesh. Our approach can be reliably applied to identify locations of safe and unsafe groundwater sources with sufficient accuracy for making management decisions by solely using remotely sensed information. This work is important to evaluate levels of As exposure, impacts to public health, and to shed light on the underlying hydrogeochemical processes that drive As mobilization into groundwater.

Indexed as

ArsenicGroundwaterWater Pollutants, ChemicalAsia, SoutheasternEnvironmental MonitoringHumansArsenicWater Pollutants, Chemicalarsenicenvironmental predictive modelingfloodinggeospatial analysisgroundwater

Identifiers

PMID34951307
PMCPMC8766940

What OpenQuestion holds

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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.