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Stochastic indicator analysis of contaminated sites

Part of: Decision theory Geophysics Survival analysis and censored data Geophysics (general) Applications Stochastic processes

Published online by Cambridge University Press:  14 July 2016

George Christakos  and
Dionissios T. Hristopulos
George Christakos*
Affiliation:
University of North Carolina
Dionissios T. Hristopulos*
Affiliation:
University of North Carolina
*
∗Postal address: Department of Environmental Sciences and Engineering, University of North Carolina, CB#7400, Chapel Hill, NC 27599–7400, USA.
∗Postal address: Department of Environmental Sciences and Engineering, University of North Carolina, CB#7400, Chapel Hill, NC 27599–7400, USA.
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Abstract

We formulate stochastic indicator parameters that characterize pollution levels in geographical regions with heterogeneous contaminant distributions. The indicator parameters are expressed in terms of the random fields representing the contaminant distributions and the critical threshold level specified by health and environmental standards. Certain theoretical results are proven regarding univariate and bivariate indicator parameters. The analytical expressions obtained are general and can be used in practice for various types of contaminant distributions. A test of ergodicity-breaking is suggested for scientific and engineering applications in terms of the indicator parameters. Fractal characteristics of the indicator parameters are discussed. The effects of modelling and observation scale on exceedance contamination analysis are examined. Indicator random field parameters are studied on both continuum and lattice domains using analytical means and numerical simulations.

Keywords

RANDOM FIELDSINDICATORSLEVEL-CROSSINGLATTICE

MSC classification

Primary: 60G60: Random fields 62C99: None of the above, but in this section 62N99: None of the above, but in this section 62P99: None of the above, but in this section
Secondary: 86A05: Hydrology, hydrography, oceanography 86A32: Geostatistics
Type
Research Papers
Information
Journal of Applied Probability , Volume 34 , Issue 4 , December 1997 , pp. 988 - 1008
Copyright
Copyright © Applied Probability Trust 1997 

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