• Geotechnical Engineering
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• v.3 no.2
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• pp.17-28
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• 1987

Reliability of the cone penetration test (CPT) for estimating shear strength of marine soils is investigated in this paper. For sands, the uncertainty about the angle of internal friction is analyzed. It includes the spatial variation of the soil and the model error in the equation used for interpretation. The most serious uncertainty encountered was the error in the interpretative models. Different methods of interpretation gave quite different values. Subjective opinion was introduced to combine all the interpretative models in a systematic manner. For clays, the undrained Shear Strength from the CPT results is usually =derived by empirical correlations between cone resistance and untrained shear strength from laboratory tests or field vane tests, expressed in terms of cone factor and function of overburden pressure. The uncertainty of the undrained shear strength is caused by data scatter of the cone factor in the correlation, model error of the cone factor, effect of anisotropy, and spatial variability of cone resistance. Among these uncertainties, the most serious one was the data scatter of the cone factor in the .correlation. Between the laboratory test and the field vane test used for correlation, the field vane test was more reliable.

• Journal of Soil and Groundwater Environment
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• v.15 no.5
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• pp.8-15
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• 2010

The purpose of this research is to check the validation of an auto-analysis method combined with aqua regia digestion apparatus for improvement of water distillation method used as a fluorine test of soil. Fluorine contents of CaO used in the pretreatment course of water distillation method were 120 mg/kg ~ 5,064 mg/kg at the blank test, which was exceeded up to maximum 12.5 times of the soil standard, so it was estimated due to a effect of fluorine existing as impurities of CaO. The recovery test of the same samples indicated that water distillation method and auto-analysis method were 134.5mg/kg and 161.7mg/kg respectively, the recovery ratio of the latter was 16.8% higher than the formal. The validation test of two methods satisfied the standard, but auto analysis method was excellent more than distillation method. Also, auto analysis method could save a analysis time up to maximum 4.7 times by comparison with water distillation method.

• Journal of Soil and Groundwater Environment
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• v.16 no.6
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• pp.1-9
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• 2011

A bibliographical review of Gy sampling theory for particulate materials was conducted to provide readers with useful means to reduce errors in soil contamination investigation. According to the Gy theory, the errors caused by the heterogeneous nature of soil include; the fundamental error (FE) caused by physical and chemical constitutional heterogeneity, the grouping and segregation error (GE) aroused from gravitational force, long-range heterogeneous fluctuation error ($CE_2$), the periodic heterogeneity fluctuation error ($CE_3$), and the materialization error (ME) generated during physical process of sample treatment. However, the accurate estimation of $CE_2$ and $CE_3$ cannot be estimated easily and only increasing sampling locations can reduce the magnitude of the errors. In addition, incremental sampling is the only method to reduce GE while grab sampling should be avoided as it introduces uncertainty and errors to the sampling process. Correct preparation and operation of sampling tools are important factors in reducing the incremental delimitation error (DE) and extraction error (EE) which are resulted from physical processes in the sampling. Therefore, Gy sampling theory can be used efficiently in planning a strategy for soil investigations of non-volatile and non-reactive samples.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.888-895
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• 2009

Compaction is a process of increasing soil density using physical energy. It is intended to improve the strength and stiffness of soil. In embankment, degree of compaction affects the construction time, money, also method of soil improvement. In large scale embankment project, difficulties of embankment should change due to uncertainty of settlement. So it is very important to predict the final settlement and factor of safety induced by embankment. In many construction site, there are primarily design of high embankment using in-situ soil. Therefore numerical analyses are necessary for valid evaluation of the settlement prediction. But due to the construction cost and schedule, there were lacking in properties of soil and also limited number of in-situ test were performed. So we proposed the method that can easily estimate the proper soil parameters and suggest the proper method of numerical analysis. From this, two-dimensional finite-difference numerical analysis was conducted to investigate the settlement and factor of safety induced by embankment with various case of compaction rate and embankment height.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.4
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• pp.657-661
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• 2011

The chlorinated dioxins and furans have attracted considerable scientific and public concern because of their environmental persistence and super-toxicity through the foodchain. Recent dioxin scandals in several military bases have also contributed to a higher awareness on the side of food consumers as well as foodwaste combustion. However, there is continuing uncertainty over the relative importance of different sources of dioxins and furans to the soil environment. In difference to those awareness there is a main influence of potential soil contamination on the dioxin contents in groundwater. It is, therefore, important to provide a sound scientific framework and basis by which to evaluate the significance of the presence of dioxin in soils. Consequently, we have to identify the characteristics and nature of dioxin released into the soil environment, especially in agricultural aspect.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.4
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• pp.246-254
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• 2015

This study explored the effect of rainfall pattern and soil characteristics on water management in rice paddy fields, using a soil water balance model, BUDGET. In two sites with different soil textural group, coarse loamy soil (Gangseo series) and fine soil (Hwadong series), respectively, we have monitored daily decrease of water depth, percolation rate, and groundwater table. The observed evapotranspiration (ET) was obtained from differences between water depth decrease and percolation rate. The root mean square difference values between observed and BUDGET-estimated ET ranged between 10% and 20% of the average observed ET. This is comparable to the measurement uncertainty, suggesting that the BUDGET model can provide reliable ET estimation for rice fields. In BUDGET model of this study, irrigation requirement was determined as minimum water need for maintaining water-saturated soil surface, assuming 100 mm of bund height and no lateral loss of water. The model results showed different water balance and irrigation requirement with the different soil profile and indicated that minimum percolation rate by plow pan could determine the irrigation requirement of rice paddy field. For the condition of different rainfall distribution, the results presented different irrigation period and amounts, representing the importance of securing water for irrigation against different rainfall pattern.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.4
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• pp.43-51
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• 2007

Liquefaction-induced lateral spreading continues to be a major cause of damage to deep foundations. Currently there is a huge uncertainty associated with the maximum lateral pressures and forces applied by the liquefied soil to deep foundations. Furthermore, recent centrifuge and is shaking table tests of pile foundations indicate that the permeability of the liquefied sand is an extremely important and poorly understood factor. This article presents experimental results and analysis of one of the centrifuge tests that were conducted at the 150 g-ton RPI centrifuge to investigate the effect of soil permeability in the response of single piles and pile groups to lateral spreading.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.509-520
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• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.289-297
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• 2010

Common practice of Soil Water Assessment Tool (SWAT) model validation is to use a single variable (i.e., streamlfow) to calibrate SWAT model due to the paucity of actual hydrological measurement data in Korea. This approach, however, often causes errors in the simulated results because of numerous sources of uncertainty and complexity of SWAT model. We employed multi-variables (i.e., streamflow, evapotranspiration, and soil moisture), which were measured at mixed forest in Seolmacheon catchment ($8.54\;km^2$), in order to assess the performance and reduce the uncertainties of SWAT model output. Meteorological and surface topographical data of the catchment were obtained as basic input variables and SWAT model was calibrated using daily data of streamflow (Jan. - Dec.), evapotranspiration (Sep. - Dec.), and soil moisture (Jun. - Dec.) collected in 2007. The model performance was assessed by comparing its results with the observation (i.e., streamflow of 2003 to 2008 and evapotranspiration and soil moisture of 2008). When the multi-variable measurements were used to calibrate the SWAT model, the model results showed better agreement with the measurements compared to those using a single variable measurement by showing increases in coefficient of determination ($R^2$) from 0.72 to 0.76 for streamflow, from 0.49 to 0.59 for soil moisture, and from 0.52 to 0.59 for evapotranspiration. The findings highlight the importance of reliable and accurate collective observation data for improving performance of SWAT model and promote its facilitation for estimating more realistic hydrological cycles at catchment scale.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.3
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• pp.55-63
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• 2012

Soil properties are not random values which is represented by mean and standard deviation but show spatial correlation. Especially, soils are highly variable in their properties and rarely homogeneous. Thus, the accuracy and reliability of probabilistic analysis results is decreased when using only one random variable as design parameter. In this paper, to consider spatial variability of soil property, one-dimensional random fields of coefficient of consolidation ($C_v$) were generated based on a Karhunen-Loeve expansion. A Latin hypercube Monte Calro simulation coupled with finite difference method for Terzaghi's one dimensional consolidation theory was then used to probabilistic analysis. The results show that the failure probability is smaller when consider spatial variability of $C_v$ than not considered and the failure probability increased when the autocorrelation distance increased. Thus, the uncertainty of soil can be overestimated when spatial variability of soil property is not considered, and therefore, to perform a more accurate probabilistic analysis, spatial variability of soil property needed to be considered.