Browse > Article
http://dx.doi.org/10.5467/JKESS.2010.31.4.301

Application of Indicator Geostatistics for Probabilistic Uncertainty and Risk Analyses of Geochemical Data  

Park, No-Wook (Department of Geoinformatic Engineering, Inha University)
Publication Information
Journal of the Korean earth science society / v.31, no.4, 2010 , pp. 301-312 More about this Journal
Abstract
Geochemical data have been regarded as one of the important environmental variables in the environmental management. Since they are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations, but also to assess the uncertainty attached to the prediction for further analysis. The main objective of this paper is to exemplify how indicator geostatistics can be effectively applied to geochemical data processing for providing decision-supporting information as well as spatial distribution of the geochemical data. A whole geostatistical analysis framework, which includes probabilistic uncertainty modeling, classification and risk analysis, was illustrated through a case study of cadmium mapping. A conditional cumulative distribution function (ccdf) was first modeled by indicator kriging, and then e-type estimates and conditional variance were computed for spatial distribution of cadmium and quantitative uncertainty measures, respectively. Two different classification criteria such as a probability thresholding and an attribute thresholding were applied to delineate contaminated and safe areas. Finally, additional sampling locations were extracted from the coefficient of variation that accounts for both the conditional variance and the difference between attribute values and thresholding values. It is suggested that the indicator geostatistical framework illustrated in this study be a useful tool for analyzing any environmental variables including geochemical data for decision-making in the presence of uncertainty.
Keywords
indicator kriging; geochemical data; uncertainty; risk;
Citations & Related Records
Times Cited By KSCI : 9  (Citation Analysis)
연도 인용수 순위
1 Goovaerts, P., AvRuskin, G., Meliker, J., Slotnick, M., Jacquez, G.M., and Nriagu, J., 2005, Geostatistical modeling of the spatial variability of arsenic in groundwater of Southeast Michigan. Water Resources Research, 41, W07013, doi:10.1029/2004WR003705.   DOI
2 Journel, A.G., 1983, Non-parametric estimation of spatial distributions. Mathematical Geology, 15, 445-468.   DOI
3 Juang, K.-W. and Lee, D.-Y., 1998, Simple indicator kriging for estimating the probability of incorrectly delineating hazardous areas in a contaminated site. Environmental Science & Technology, 32, 2487-2493.   DOI
4 Ko, K.-S., Lee, J.-S., Kim, J.-G., and Lee, J., 2009, Assessments of natural and anthropogenic controls on the spatial distribution of stream water quality in Southeastern Korea. Geosciences Journal, 13, 191-200.   DOI
5 Saisana, M., Dubois, G., Chaloulakou, A., and Spyrellis, N., 2004, Classification criteria and probability risk maps: Limitations and perspectives. Environmental Science & Technology, 38, 1275-1281.   DOI
6 Saito, H. and Goovaerts, P., 2003, Selective remediation of contaminated sites using a two-level multiphase strategy and geostatistics. Environmental Science & Technology, 37, 1912-1918.   DOI   ScienceOn
7 Van Meirvenne, M. and Goovaerts, P., 2001, Evaluating the probability of exceeding a site-specific soil cadmium contamination threshold. Geoderma, 102, 75-100.   DOI
8 이진수, 서효준, 황인호, 1998, 지화학조사연구 (1:250,000 강릉도폭 광역 지화학도). 한국자원연구소, 147 p.
9 위수민, 김은효, 2009, 여수 지역에 분포하는 백악기 화강암류에 대한 지화학적 연구. 한국지구과학회지, 30, 267-281.   과학기술학회마을   DOI
10 조규성, 노열, 정덕호, 2007, 당진화력발전소의 석탄회 연안 매립과 중금속 원소의 용출에 대한 생지화학적 연구. 한국지구과학회지, 28, 112-122.
11 진명식, 2007, 국내 지화학탐사 발전사. 자원환경지질, 40, 691-698.   과학기술학회마을
12 황상기, 이평구, 2005, 지화학자료를 이용한 금.은 광산의 배태 예상지역 추정-베이시안 지구통계학과 의사나무 결정기법의 활용. 자원환경지질, 38, 663-673.
13 Barabas, N., Goovaerts, P., and Adriaens, P., 2001, Geostatistical assessment and validation of uncertainty for three-dimensional dioxin data from sediments in an estuarine river. Environmental Science & Technology, 35, 3294-3301.   DOI
14 Deutsch, C.V. and Journel, A.G., 1998, GSLIB: Geostatistical Software Library and User's Guide. Oxford University Press, NY, USA, 369 p.
15 Goovaerts, P., 1997, Geostatistics for Natural Resources Evaluation. Oxford University Press, NY, USA, 483 p.
16 Goovaerts, P., Webster, R., and Dubois, J.-P., 1997, Assessing the risk of soil contamination in the Swiss Jura using indicator geostatistics. Environmental and Ecological Statistics, 4, 31-48.   DOI
17 Goovaerts, P., Trinh, H.T., Demond, A., Franzblau, A., Garabrant, D., Gillespie, B., Lepkowski, J., and Adriaens, P., 2008, Geostatistical modeling of the spatial distribution of soil dioxins in the vicinity of an incinerator. 1. Theory and application to Midland, Michigan. Environmental Science & Technology, 42, 3648-3654.   DOI   ScienceOn
18 박노욱, 2009, 현장 조사 자료를 이용한 GIS기반 주제도 작성을 위한 단변량 크리깅 기법의 비교. 대한원격탐사학회지, 25, 321-338.   DOI
19 오석훈, 서백수, 2007, 탄성파 속도와 전기비저항 자료의 지구통계학적 복합해석에 의한 암반등급의 확률적 평가. 물리탐사, 10, 293-298.   과학기술학회마을
20 오강호, 김주용, 고영구, 윤석태, 신상은, 박배영, 문병찬, 김해경, 2003, 광주광역시 하천의 표층퇴적물에 대한 지구화학적 특성과 오염. 한국지구과학회지, 24, 346-360.   과학기술학회마을
21 오인석, 고경석, 공인철, 구민호, 2008, 금산 매립장 주변 대수층의 수리지화학적 특성 및 오염 확산 평가. 자원환경지질, 41, 657-672.   과학기술학회마을