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Groundwater Monitoring, Detection, and Compliance

Environmental Policy and Regulation

  1. Robert D. Gibbons1,
  2. Dulal K. Bhaumik2,
  3. Subhash Aryal3

Published Online: 15 JAN 2013

DOI: 10.1002/9780470057339.vnn004

Encyclopedia of Environmetrics

Encyclopedia of Environmetrics

How to Cite

Gibbons, R. D., Bhaumik, D. K. and Aryal, S. 2013. Groundwater Monitoring, Detection, and Compliance. Encyclopedia of Environmetrics. 3.

Author Information

  1. 1

    University of Chicago, IL, USA

  2. 2

    University of Illinois at Chicago, Chicago, IL, USA

  3. 3

    University of North Texas Health Science Center, Fort Worth, TX, USA

Publication History

  1. Published Online: 15 JAN 2013

Abstract

An overview of statistical issues and methods is provided relevant to the analysis of groundwater detection and compliance-monitoring problems. The rich methodology that has been used in this area goes well beyond groundwater monitoring applications to many other areas of interest in environmental monitoring and statistics. First, we provide an overview of statistical prediction limits for normal, lognormal, and gamma random variables, as well as nonparametric alternatives. Issues related to multiple comparisons, censored data, nonnormality, and verification sampling (i.e., sequential testing) are considered in the statistical developments. Second, we provide an overview of statistical methods that are relevant for compliance monitoring, where interest is often focused on whether on-site average concentrations exceed a health-based regulatory standard. This leads to discussion of a variety of statistical approaches based on confidence limits for normal and nonnormal distributions and nonparametric alternatives. A distinction is made between assessment monitoring where the null hypothesis is that contamination is not present and corrective action monitoring where the null hypothesis is that contamination is present.

Keywords:

  • prediction limits;
  • verification resampling;
  • background measurements;
  • downgradient;
  • nondetects