Spatial modeling for groundwater arsenic levels in North Carolina.


Journal Article

To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area.

Full Text

Duke Authors

Cited Authors

  • Kim, D; Miranda, ML; Tootoo, J; Bradley, P; Gelfand, AE

Published Date

  • June 2011

Published In

Volume / Issue

  • 45 / 11

Start / End Page

  • 4824 - 4831

PubMed ID

  • 21528844

Pubmed Central ID

  • 21528844

Electronic International Standard Serial Number (EISSN)

  • 1520-5851

International Standard Serial Number (ISSN)

  • 0013-936X

Digital Object Identifier (DOI)

  • 10.1021/es103336s


  • eng