Evidence map›Paper›PMID 38575591›Full record

ArticleScientific data2024

A database of groundwater wells in the United States.

Chung-Yi Lin, Alexandra Miller, Musab Waqar, Landon T Marston

Abstract readDataset
In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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.

Chung-Yi LinDepartment of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA.ORCID http://orcid.org/0000-0002-9464-4696
Alexandra MillerDepartment of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA.
Musab WaqarDepartment of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA.
Landon T MarstonDepartment of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA. lmarston@vt.edu.ORCID http://orcid.org/0000-0001-9116-1691

Funding

Department of the Interior | U.S. Geological Survey (United States Geological Survey) G23AC00071-00Foundation for Food and Agriculture Research (FFAR) FF-NIA19-0000000084National Science Foundation (NSF) 2108196National Science Foundation (NSF) 2144169
6 · The paper itself

Abstract

Groundwater wells are critical infrastructure that enable the monitoring, extraction, and use of groundwater, which has important implications for the environment, water security, and economic development. Despite the importance of wells, a unified database collecting and standardizing information on the characteristics and locations of these wells across the United States has been lacking. To bridge this gap, we have created a comprehensive database of groundwater well records collected from state and federal agencies, which we call the United States Groundwater Well Database (USGWD). Presented in both tabular form and as vector points, USGWD comprises over 14.2 million well records with attributes, such as well purpose, location, depth, and capacity, for wells constructed as far back as 1763 to 2023. Rigorous cross-verification steps have been applied to ensure the accuracy of the data. The USGWD stands as a valuable tool for improving our understanding of how groundwater is accessed and managed across various regions and sectors within the United States.

Identifiers

PMID38575591
PMCPMC10995170

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.