• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.04a
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• pp.316-319
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• 2005

Contaminated area should be identified for designing polluted groundwater cleanup plan. A methodology was suggested to identify a contaminant plume distribution geostatistically. James & Gorelick (1994) suggested a methodology to evaluate data worth as expected reducing remediation cost. In this study, their methodology was modified to evaluate data worth as expected reducing uncertainty of the contaminant plume distribution. In suggested methodology, the source identification model by Mahar & Datta (2001) using a forward solute transport model is integrated. Suggested methodology was assessed by two simple example problems and its result represented reducing uncertainties of contaminant plume distribution successfully.

• Korean Journal of Hydrosciences
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• v.6
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• pp.39-49
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• 1995

The surface hydrology of large land areas is susceptible to several preferred stable states with transitions between stable states induced by stochastic fluctuation. This comes about due to the close couping of land surface and atmospheric interaction. An interesting and important issue is the duration of residence in each mode. Mean transition times between the stable modes are analyzed for different model parameters or climatic types. In an example situation of this differential equation exhibits a bimodal probability distribution of soil moisture states. Uncertainty analysis regarding the model parameters is performed using a Monte-Carlo simulation method. The method developed in this research may reveal some important characteristics of soil moisture or precipitation over a large area, in particular, those relating to abrupt change in soil moisture or preciptation having extremely variable duration.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.10a
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• pp.344-351
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• 2005

In this paper, a reliability-groundwater flow program is developed by coupling the 2-D finite element numerical groundwater flow program with first and second order reliability program. From the parametric study of hydraulic conductivity of soil layers, the increase of both mean and variance of hydraulic conductivity results in the increase of probability of exceeding the threshold hydraulic head. The probability of failure was more sensitive to parameters of weathered granitic soil and rock located at the middle and bottom of the excavation than those at the other locations. It can be recommended from this study that the reliability method, which can include the uncertainty of soil parameters, should be performed together with the deterministic analysis to compensate the weakness of the latter analysis for the groundwater flow problem of underground excavations.

• Journal of the Korean Geotechnical Society
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• v.24 no.8
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• pp.111-123
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• 2008

Geotechnical engineering problems are characterized by many sources of uncertainty. Some of these sources are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for a probabilistic analysis that considers the spatial variability of soil properties is presented to study the response of spatially random soil. The approach integrates a commercial finite difference method and random field theory into the framework of a probabilistic analysis. Two-dimensional non-Gaussian random fields are generated based on a Karhunen-$Lo{\grave{e}}ve$ expansion in a fashion consistent with a specified marginal distribution function and an autocorrelation function. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses were performed to study the effects of uncertainty due to the spatial heterogeneity on the settlement and bearing capacity of a rough strip footing. The simulations provide insight into the application of uncertainty treatment to the geotechnical problem and show the importance of the spatial variability of soil properties with regard to the outcome of a probabilistic assessment.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.23-30
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• 2000

A calculation technique which estimates natural recharge was proposed and prepared with the existing techniques. And the necessity to obtain representative averages of 'specific yield' was discussed.

• Computational Structural Engineering
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• v.28 no.3
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• pp.18-27
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• 2015

• Journal of the Korean Geotechnical Society
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• v.27 no.7
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• pp.59-68
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• 2011

Subsurface Investigation results always reflect a level of soil uncertainty, which sometimes requires statistical corrections of the data for the appropriate engineering decision. This study suggests a closed-form framework to extract the outlying data points from the testing results using the statistical geo-spatial information analyses with outlier analysis and kring-based crossvalidation. The suggested analysis method is conducted to soil stratification using the borehole data in Yeouido.

• Journal of the Korean Geotechnical Society
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• v.21 no.3
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• pp.5-17
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• 2005

Spatial uncertainty of Busan marine clay ground, which commonly occurs during site investigation testing, data analysis and transformation modeling, has been described. In this paper geotechnical uncertainty of shear strength indicator $N_k$ has been quantified in both horizontal direction and vertical direction using geostatistical Kriging method. Most of soil data used are from 25 boring tests, 75 laboratory tests, 124 field vane tests and 25 cone penetration tests (CPT). CPT-$N_k$ data for undrained shear strength determination, which are the most important properties in geotechnical design stages, have been analysed. Comparison between cone factor from conventional CPT-based method and that of geostatistical method shows that geostatistical Kriging method is an ideal tool to quantify the spatial variability of uncertainty from self-correlation of soil property of interest, and can be recommended to identify the spatial distribution of consolidation .md shear strength of soils at any sites concerned.

• Journal of Soil and Groundwater Environment
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• v.9 no.1
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• pp.28-38
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• 2004

This study presents the result of uncertainty and sensitivity analysis of a pharmacokinetic model which describes the distribution and removal of benzene at each organ when an indivisual inhales indoor contaminated air with benzene originated from groundwater. The pharmacokinetic model simulates the distribution of benzene deposited in organs of human body through inhalation of contaminated indoor air as well as degradation-metabolism in liver. This study focused on the uncertainty problem induced from the use of the single values for blood flow, partition coefficient, degradation constant, volume, etc. of each organ which was due to a lack of knowledge about these parameters or their measurements. To solve this problem, uncertainty analysis on the pharmacokinetic model was conducted simultaneously which would help understanding the risk assessment associated with VOCs.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.307-316
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• 2019

In the agricultural sector, greenhouse gas emissions vary depending on the interaction of all ecosystem changes such as soil environment, weather environment, crop growth, and anthropogenic farming activities. Agricultural sector greenhouse gas emissions resulting from many of these interactions are highly variable. Uncertainty-based evaluation that defines the interval with confidence level of greenhouse gas emission and absorption is necessary to take account of the variance characteristics of individual emissions, but research on uncertainty evaluation method is insufficient. This study aims to decide on the effect of reducing N₂O emissions from upland soils using an uncertainty-based approach. An uncertainty-based approach confirmed whether there was a difference between confidence intervals in the 5 different fertilizer treatment groups to reduce greenhouse gas emissions. Unlike the statistically significant test with three repetition averages, the uncertainty-based approach method estimated in this study is able to estimate the confidence interval considering the distribution characteristics of the emissions, such as the dispersion characteristics of individual emissions. Therefore, it is considered that the reliability of emissions can be improved by statistically testing the variance characteristics of emissions such as the uncertainty-based approach. It is hoped that the direction of the uncertainty-based approach for the effect of reducing greenhouse gas emissions in agriculture will be helpful in the future development of agricultural greenhouse gas emission reduction technology, adaptation to climate change, and further development of sustainable eco-social system.