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Kriging for estimating spatial pattern of contaminants: Potential and problems
1Statistics Section, Pacific Northwest Laboratory, 99352, Richland, Washington.
Environmental Monitoring and Assessment
|November 22, 2013
Summary
This study demonstrates kriging techniques for mapping soil contaminant spatial patterns. Lognormal kriging accurately estimates radionuclide concentrations and inventory, but requires careful spatial correlation modeling to avoid bias.
Area of Science:
- Geostatistics
- Environmental Science
- Geochemistry
Background:
- Kriging is a geostatistical method for spatial interpolation.
- Estimating contaminant distribution in soil is crucial for environmental assessment.
- Accurate spatial modeling is essential for reliable environmental data interpretation.
Purpose of the Study:
- To illustrate the application of kriging techniques for estimating contaminant spatial patterns in soil.
- To review the assumptions, advantages, and disadvantages of kriging.
- To demonstrate lognormal kriging using radionuclide soil concentration data.
Main Methods:
- Review of kriging assumptions and limitations.
- Application of lognormal kriging (kriging on log-transformed data).
- Spatial correlation structure analysis and modeling.
Main Results:
- Lognormal kriging effectively estimates average concentrations, concentration contours, and radionuclide inventory.
- Confidence bands for concentration contours were generated.
- Bias in estimates was observed when spatial correlation structure was not accurately modeled.
Conclusions:
- Kriging, particularly lognormal kriging, is a valuable tool for environmental contaminant assessment.
- Accurate modeling of spatial correlation is critical for valid kriging estimates.
- Ignoring spatial correlation variations can lead to biased results in environmental studies.
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