• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.1
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• pp.217-229
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• 1994

A probabilistic method was employed to compare the prediction accuracy of axial and volumetric strains of Lade's double surface model with that of single surface model. Several experiments were conducted to examine the variabilities of soil parameters for two models using Back-ma river sand. Mean values and standard deviations of soil parameters obtained from experimental data were used for the evaluation of the uncertainty of analyzed strains by the first order approximation. It is shown that the variabilities of parameters in the single surface model are more consistent than those of the double surface model. However, in the accuracy of axial strain by probabilistic analysis, double surface model is more stable than single surface model. It is also shown that two models are excellent in view of the accuracy of the volumetric strain. The method given in this paper may be effectively utilized to estimate the constitutive model because other results of the comparison of two models coincide with those of this paper.

• Journal of Soil and Groundwater Environment
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• v.21 no.4
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• pp.30-41
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• 2016

The amount of groundwater related data is drastically increasing domestically from various sources since 2000. To justify the more expansive continuation of the data acquisition and to derive valuable implications from the data, continued employments of sophisticated and state-of-the-arts statistical tools in the analyses and predictions are important issue. In the present study, we employed a well established machine learning technique of Gaussian Process Regression (GPR) model in the trend analyses of groundwater level for the long-term change. The major benefit of GPR model is that the model provide not only the future predictions but also the associated uncertainty. In the study, the long-term predictions of groundwater level from the stations of National Groundwater Monitoring Network located within Han River Basin were exemplified as prediction cases based on the GPR model. In addition, a few types of groundwater change patterns were delineated (i.e., increasing, decreasing, and no trend) on the basis of the statistics acquired from GPR analyses. From the study, it was found that the majority of the monitoring stations has decreasing trend while small portion shows increasing or no trend. To further analyze the causes of the trend, the corresponding precipitation data were jointly analyzed by the same method (i.e., GPR). Based on the analyses, the major cause of decreasing trend of groundwater level is attributed to reduction of precipitation rate whereas a few of the stations show weak relationship between the pattern of groundwater level changes and precipitation.

• Journal of Soil and Groundwater Environment
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• v.21 no.6
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• pp.67-79
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• 2016

Gaussian process regression (GPR) is proposed as a tool of long-term groundwater quality predictions. The major advantage of GPR is that both prediction and the prediction related uncertainty are provided simultaneously. To demonstrate the applicability of the proposed tool, GPR and a conventional non-parametric trend analysis tool are comparatively applied to synthetic examples. From the application, it has been found that GPR shows better performance compared to the conventional method, especially when the groundwater quality data shows typical non-linear trend. The GPR model is further employed to the long-term groundwater quality predictions based on the data from two domestically operated groundwater monitoring stations. From the applications, it has been shown that the model can make reasonable predictions for the majority of the linear trend cases with a few exceptions of severely non-Gaussian data. Furthermore, for the data shows non-linear trend, GPR with mean of second order equation is successfully applied.

• Journal of the Korean association of regional geographers
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• v.17 no.2
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• pp.245-258
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• 2011

Best management practices (BMPs) are widely accepted and implemented as a mitigation method for soil erosion and non-point source problems. Estimating the amount of soil erosion and the effectiveness of BMPs using hydrological models help to understand the condition, identify the problems, and make plans for conservation practices in an area, typically a watershed. However, the accuracy and reliability of assessment of BMP impacts estimated by hydrological models can be often questionable due to the uncertainties from various sources including GIS(Geographic Information System) data, scale, and model. This study reviewed the development and the background of hydrological models, and the modeling issues such as the selection of models, scale, and uncertainties of data and models. This study also discussed the advantage of a small scale and spatially distributed model to estimate the impacts of BMPs.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.73-76
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• 2008

The damage of earthquakes have to achieve by probabilistic evaluation because of uncertainty of earthquake. Fragility analysis is a useful tool for predicting the probability of damage induced by the probable earthquake. This paper presents the probability of damage as a function of peak ground acceleration and estimates the probability of five damage levels for the pier of prestressed concrete (PSC) bridge subjected to given ground acceleration. At each 100 artificial earthquake motions were generated in terms of soil conditions, and nonlinear time domain analyses were performed for the damage states of the pier of PSC bridge structures. These damage states are described by displacement ductility result from seismic performance based on existing research results. Using the damage states and ground motion parameters, five fragility curves for the pier of PSC bridges with five types of dominant frequencies were constructed assuming a log-nomal distribution. It was found that there was a significant effect on the fragility curves due to the dominant frequencies.

• Journal of Korea Water Resources Association
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• v.47 no.1
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• pp.71-82
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• 2014

The objective of this study is to project and analyze drought conditions using future climate and hydrology information over South Korea. This study used three Global Climate Models (GCMs) and three hydrological models considering the uncertainty of future scenario. Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI) and Standardized Soil moisture Index (SSI) classified as meteorological, hydrological and agricultural droughts were estimated from the precipitation, runoff and soil moisture. The Mann-Kendall test showed high increase in future drought trend during spring and winter seasons, and the drought frequency of SRI and SSI is expected higher than that of SPI. These results show the high impact of climate change on hydrological and agriculture drought compared to meteorological drought.

• Journal of the Korean Geotechnical Society
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• v.18 no.5
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• pp.281-293
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• 2002

Empiricism has characterized the traditional methods of pile design; in essence, pile design recommendations are based on the accumulated knowledge of pile behaviour based on the construction and subsequent load testing of piles in soil and rock. In this paper, the traditional approaches to design of piles in rock will be briefly reviewed. It will be shown that the unrelated empirical relationships developed fur rock lead to considerable uncertainty in the design of piles. A new method for predicting the shaft resistance of piles socketed into rock, and based on fundamental principles is outlined. It is shown that the shaft resistance predictions of this method agree well with the field test data for rock and hard soil. It is demonstrated by way of a limited parametric study that shaft roughness and socket diameter are critical factors in the performance of piles constructed in these materials. The application of the method to piles socketed into the granites and gneisses of Korea is discussed by way of a case study and by reference to recent direct shear tests on these rocks.

• Journal of Korea Water Resources Association
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• v.51 no.7
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• pp.585-597
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• 2018

This study aims to investigate the variation of water quality and discharge under the condition of climate change and Best Management Practices (BMPs), which is one of the reduction methods for non-point source pollution. Soil and Water Assessment Tool (SWAT) model is applied to case in Cheongmicheon watershed. The coefficients required for SWAT model were calibrated using SWAT Calibration and Uncertainty Program. Climate change is considered by using Representative Concentration Pathway (RCP) scenarios, RCP 4.5 and RCP 8.5. It is known from simulation results that the non-point source pollutant increases under the climate change scenario assuming worse condition. It is also found in this study that an appropriate application of BMPs is able to reduce the quantity and temporal variation of non-point source pollutant effectively.

• Journal of Soil and Groundwater Environment
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• v.25 no.2_spc
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• pp.28-54
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• 2020

Even though a systematic sampling approach is very crucial in both the general and detailed investigation phases to produce the best conceptual site model for contaminated sites, the concept is not yet established in South Korea. The U.S. Environmental Protection Agency (EPA) issued the 'Strategic Sampling Approaches Technical guide' in 2018 to help environmental professionals choose which sampling approaches may be needed and most effective for given site conditions. The EPA guide broadly defines strategic sampling as the application of focused data collection across targeted areas of the conceptual site model (CSM) to provide the appropriate amount and type of information needed for decision-making. These strategic sampling approaches can prevent the essential data from missing, minimize the uncertainty of projects and secure the data which are necessary for the important site-decisions. Furthermore, these provide collaborative data sets through the life cycle phases of projects, which can generate more positive proofs on the site-decisions. The strategic sampling approaches can be divided by site conditions. This technical guide categorized it into eight conditions; High-resolution site characterization in unconsolidated environments, High-resolution site characterization in fractured sedimentary rock environments, Incremental sampling, Contaminant source definition, Passive groundwater sampling, Passive sampling for surface water and sediment, Groundwater to surface water interaction, and Vapor intrusion. This commentary paper introduces specific sampling methods based on site conditions when the strategic sampling approaches are applied.

• Journal of Soil and Groundwater Environment
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• v.27 no.spc
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• pp.64-74
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• 2022

The conceptual site model (CSM) is used as a key tool to support decision making in risk based management of contaminated sites. In this work, CSM was applied in Jeonju Industrial Complex where site investigation for groundwater contamination was conducted. Site background information including facility types, physical conditions, contaminants spill history, receptor exposure, and ecological information were collected and cross-checked with tabulated checklist necessary for CSM application. The CSM for contaminants migration utilized DNAPL transport model and narrative CSMs were constructed for source to receptor pathway, ecological exposure route, and contaminants fate and transport in the form of a diagram or flowchart. The component and uncertainty of preliminary CSM were reviewed using the data gap analysis while taking into account the purpose of the survey and the site management stage at the time of the survey. Through this approach, the potential utility of CSM was demonstrated in the site management process, such as assessing site conditions and planning follow-up survey work.