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Virginia Tech

Survey of Groundwater Wells in the United States

Abstract

dc:description.abstract

Groundwater wells are critical infrastructure with significant impacts on the environment, water availability, and economy. However, comprehensive data on the purposes, locations, depths, and construction of these wells are only collected by individual states. We have compiled a nationwide dataset of groundwater wells throughout the United States. The tabular dataset consists of all groundwater well data obtained from the states, containing over nine million records. A subset of this dataset was created that excludes wells located outside of the reported county or state, with over eight million records. Our dataset represents all known groundwater well locational data that states could release. The data made available by these datasets can serve as a critical tool for refining our understanding of how groundwater is accessed and used throughout the United States, and how it impacts different industries.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Civil Engineering
Department dc:contributor.department
Civil and Environmental Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2023

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Miller, Alexandra Leigh
Chair dc:contributor.committeechair
  • Marston, Landon T.
Committee members dc:contributor.committeemember
  • Saksena, Siddharth
  • Shortridge, Julie Elizabeth

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:37826
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/115598

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Miller, Alexandra Leigh. Survey of Groundwater Wells in the United States. masters thesis, Virginia Tech, 2023. http://hdl.handle.net/10919/115598