Geostatistical modeling and mapping of sediment contaminant concentrations

Kandiah Ramanitharan, Laura J. Steinberg, Gerhard Piringer

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

This paper demonstrates the application of geostatistical modeling techniques to the quantification of Aroclors and heavy metals in Hudson and Duwamish river sediments, respectively. The objective was to compare models and modeling parameters between contaminants and sites, as well as to investigate a modeling modification that may accomodate curved river segments. Gaussian, exponential and spherical variograms were used to model micro-scale spatial correlations, and ordinary kriging and simple kriging were used as interpolation techniques. The major macro-anisotropy direction paralleled the river flow at both sites. The macro-anisotropy ratio was comparable between Aroclors, but varied between the metals. Comparable results for Aroclors could be due to similar physico-chemical properties governing fate and transport processes. Generally, spherical and exponential variograms fitted the data better than Gaussian variograms at both sites. With the exception of comparable micro-anisotropy parameters between the Aroclors, variogram parameters varied between contaminants and sites. Subdividing curved river segments and modeling the reaches separately did not improve predictions. Expanding the study to other types of water bodies and research into the use of co-kriging promises further insights.

Original languageEnglish (US)
Title of host publicationContaminated Soils, Sediments and Water
PublisherSpringer US
Pages565-583
Number of pages19
Volume9
ISBN (Print)038723036X, 9780387230368
DOIs
StatePublished - Dec 1 2005
Externally publishedYes

Keywords

  • Contaminated Sediments
  • GIS
  • Geostatistics
  • Hotspots
  • River

ASJC Scopus subject areas

  • Environmental Science(all)
  • Earth and Planetary Sciences(all)

Fingerprint Dive into the research topics of 'Geostatistical modeling and mapping of sediment contaminant concentrations'. Together they form a unique fingerprint.

  • Cite this

    Ramanitharan, K., Steinberg, L. J., & Piringer, G. (2005). Geostatistical modeling and mapping of sediment contaminant concentrations. In Contaminated Soils, Sediments and Water (Vol. 9, pp. 565-583). Springer US. https://doi.org/10.1007/0-387-23079-3_37