Journal of Soil and Groundwater Environment (한국지하수토양환경학회지:지하수토양환경)

Korean Society of Soil and Groundwater Environment (한국지하수토양환경학회)
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Evaluation of Geostatistical Approaches for better Estimation of Polluted Soil Volume with Uncertainty Evaluation

지구통계 기법을 활용한 토양 오염범위 산정 및 불확실성 평가

  • Kim, Ho-Rim (KU-KIST Green School (Graduate School of Energy and Environment) and Department of Earth and Environmental Sciences, Korea University) ;
  • Kim, Kyoung-Ho (KU-KIST Green School (Graduate School of Energy and Environment) and Department of Earth and Environmental Sciences, Korea University) ;
  • Yun, Seong-Taek (KU-KIST Green School (Graduate School of Energy and Environment) and Department of Earth and Environmental Sciences, Korea University) ;
  • Hwang, Sang-Il (Korea Environment Institute (KEI)) ;
  • Kim, Hyeong-Don (National Instrumentation Center for Environmental Management College of Agriculture and Life Sciences, Seoul National University) ;
  • Lee, Gun-Taek (National Instrumentation Center for Environmental Management College of Agriculture and Life Sciences, Seoul National University) ;
  • Kim, Young-Ju (Korea Environment Institute (KEI))
  • 김호림 (고려대학교 그린스쿨대학원(KU-KIST) 및 지구환경과학과) ;
  • 김경호 (고려대학교 그린스쿨대학원(KU-KIST) 및 지구환경과학과) ;
  • 윤성택 (고려대학교 그린스쿨대학원(KU-KIST) 및 지구환경과학과) ;
  • 황상일 (한국환경정책.평가연구원) ;
  • 김형돈 (서울대학교 농생명과학공동기기원(NICEM)) ;
  • 이군택 (서울대학교 농생명과학공동기기원(NICEM)) ;
  • 김영주 (한국환경정책.평가연구원)
  • Received : 2012.11.09
  • Accepted : 2012.12.03
  • Published : 2012.12.31
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Abstract

Diverse geostatistical tools such as kriging have been used to estimate the volume and spatial coverage of contaminated soil needed for remediation. However, many approaches frequently yield estimation errors, due to inherent geostatistical uncertainties. Such errors may yield over- or under-estimation of the amounts of polluted soils, which cause an over-estimation of remediation cost as well as an incomplete clean-up of a contaminated land. Therefore, it is very important to use a better estimation tool considering uncertainties arising from incomplete field investigation (i.e., contamination survey) and mathematical spatial estimation. In the current work, as better estimation tools we propose stochastic simulation approaches which allow the remediation volume to be assessed more accurately along with uncertainty estimation. To test the efficiency of proposed methods, heavy metals (esp., Pb) contaminated soil of a shooting range area was selected. In addition, we suggest a quantitative method to delineate the confident interval of estimated volume (and spatial extent) of polluted soil based on the spatial aspect of uncertainty. The methods proposed in this work can improve a better decision making on soil remediation.

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References

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