Probabilistic evaluation of spatial distribution of secondary compression by using kriging estimates of geo-layers

Woojin Lee, Donghee Kim, Youngho Chae, Dongwoo Ryu

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14 Citations (Scopus)


This paper presents a procedure for evaluating the spatial uncertainty in the secondary compression (ss) using a probabilistic method. In order to evaluate the spatial distribution of ss, the spatial maps of three geo-layers (the thickness and depth of the consolidating layer, the bottom elevation of the reclaimed sandfill) are estimated by using kriging techniques. For all three geo-layers considered in this study, the ordinary kriging is found to give more reliable estimates than the kriging with a trend and simple kriging. It is observed that the coefficients of variation (COVs) of Cα/Cc and Cc/(1+e0) have similar influences on the COV of ss. It is also shown that the COV of cv has less effect on the COV of ss than the COVs of Cα/Cc and Cc/(1+e0) although the COV of cv is larger than that of Cα/Cc and Cc/(1+e0). The COV of ss evaluated by considering all the COVs of soil properties is 0.420, which is 1.4-2.7 times larger than that determined by considering the COV of an individual soil property separately. It is observed that the area exceeding a design criterion increases as the COV of Cα/(1+e0) increases and the probabilistic design criterion (α) decreases. For Songdo New City, the area ratio decreases from 0.47 for α value of 0.05 to 0.04 for α value of 0.45. The design procedure presented in this paper could be used in the decision making process for a geotechnical engineering design.

Original languageEnglish
Pages (from-to)239-248
Number of pages10
JournalEngineering Geology
Issue number3-4
Publication statusPublished - 2011 Oct 10

Bibliographical note

Funding Information:
This paper was supported by a POSCO E&C grant, and was supported by the Basic Research Project of the Korea Institute of Geoscience and Mineral Resources (KIGAM) ( GP2009-019 ) funded by the Ministry of Science and Technology of Korea .


  • Coefficient of variation
  • Kriging
  • Probabilistic method
  • Secondary compression

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Geology


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