• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.920-924
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• 2012

This study was performed to estimate total contents of arsenic (As) by stepwise multiple-regression analysis using chemical properties and extractable contents of metal in paddy soil adjacent to abandoned mines. The soil was collected from paddies near abandoned mines. Soil pH, electrical conductively (EC), organic mater (OM), available phosphorus ($P_2O_5$), and exchangeable cations (Ca, K, Mg, Na) were measured. Total contents of As and extractable contents of metals were analyzed by ICP-OES. From stepwise analysis, it was showed that the contents of extractable As, available phosphorus, extractable Cu, exchangeable K, exchangeable Na, and organic mater significantly influenced the total contents of As in soil (p<0.001). The multiple linear regression models have been established as Log (Total-As) = 0.741 + 0.716 Log (extractable-As) - 0.734 Log (avail-$P_2O_5$) + 0.334 Log (extractable-Cu) + 0.186 Log (exchangeable-K) - 0.593 Log (exchangeable-Na) + 0.558 Log (OM). The estimated value in total contents of As was significantly correlated with the measured value in soil ($R^2$=0.84196, p<0.0001). This predictive model for estimating total As contents in paddy soil will be properly applied to the numerous datasets which were surveyed with extractable heavy metal contents based on Soil Environmental Conservation Act before 2010.

• Journal of the Earthquake Engineering Society of Korea
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• v.14 no.5
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• pp.1-12
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• 2010

This study presents a finite element analysis method that can accurately evaluate the nonlinear behaviour of structures affected by shallow soft subsoils and the soil-structure interaction. A two-dimensional finite element model that consists of a structure and shallow soft subsoil was used. The finite element model was used for a nonlinear time domain analysis of the OpenSees program. A parametric study was performed to investigate the effects of soil shear velocities, earthquake input motions, soft soil depth, and soil-structure interaction. The result of the proposed nonlinear finite element analysis method was compared with the result of an existing frequency domain analysis method, which is frequently used for addressing nonlinear soil behavior. The result showed that the frequency domain analysis, which uses equivalent secant soil stiffness and does not address the soil-structure interaction, significantly overestimated the response of the structures with short dynamic periods. The effect of the soil-structure interaction on the response spectrum did not significantly vary with the foundation dimensions and structure mass.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.1-8
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• 2019

Developing reliable soil moisture prediction techniques at agricultural regions is a pivotal issue for sustaining stable crop productions. In this study, a physically-based SWAP(Soil-Water-Atmosphere-Plant) model was suggested to estimate soil moisture dynamics at the study sites. ROSETTA was also integrated to derive the soil hydraulic properties(${\alpha}$, n, ${\Theta}_r$, ${\Theta}_s$, $K_s$) as the input variables to SWAP based on the soil information(Sand, Silt and Clay-SSC, %). In order to predict the soil moisture dynamics in future, the mid-term TIGGIE(THORPEX Interactive Grand Global Ensemble) and long-term S2S(Subseasonal to Seasonal) weather forecasts were used, respectively. Our proposed approach was tested at the six study sites of RDA(Rural Development Administration). The estimated soil moisture values based on the SWAP model matched the measured data with the statistics of Root Mean Square Error(RMSE: 0.034~0.069) and Temporal Correlation Coefficient(TCC: 0.735~0.869) for validation. When we predicted the mid-/long-term soil moisture values using the TIGGE(0~15 days)/S2S(16~46 days) weather forecasts, the soil moisture estimates showed less variations during the TIGGE period while uncertainties were increased for the S2S period. Although uncertainties were relatively increased based on the increased leading time of S2S compared to those of TIGGE, these results supported the potential use of TIGGE/S2S forecasts in evaluating agricultural drought. Our proposed approach can be useful for efficient water resources management plans in hydrology, agriculture, etc.

• Geomechanics and Engineering
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• v.27 no.5
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• pp.465-479
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• 2021

One of the important causes of building and infrastructure failure, such as bridges on pile foundations, is the placement of the piles in liquefiable soil that can become unstable under seismic loads. Therefore, the overarching aim of this study is to investigate the seismic behavior of a soil-pile system in liquefiable soil using three-dimensional numerical FEM analysis, including soil-pile interaction. Effective parameters on concrete pile response, involving the pile diameter, pile length, soil type, and base acceleration, were considered in the framework of finite element non-linear dynamic analysis. The constitutive model of soil was considered as elasto-plastic kinematic-isotropic hardening. First, the finite element model was verified by comparing the variations on the pile response with the measured data from the centrifuge tests, and there was a strong agreement between the numerical and experimental results. Totally 64 non-linear time-history analyses were conducted, and the responses were investigated in terms of the lateral displacement of the pile, the effect of the base acceleration in the pile behavior, the bending moment distribution in the pile body, and the pore pressure. The numerical analysis results demonstrated that the relationship between the pile lateral displacement and the maximum base acceleration is non-linear. Furthermore, increasing the pile diameter results in an increase in the passive pressure of the soil. Also, piles with small and big diameters are subjected to yielding under bending and shear states, respectively. It is concluded that an effective stress-based ground response analysis should be conducted when there is a liquefaction condition in order to determine the maximum bending moment and shear force generated within the pile.

• Geomechanics and Engineering
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• v.34 no.5
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• pp.577-595
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• 2023

A dynamic triaxial discrete element numerical model of lightweight soil was established using the discrete element method to study the microscopic mechanism of expanded polystyrene (EPS) particles in the soil under cyclic loading. The microscopic parameters of the discrete element model of the lightweight soil were calibrated depending on the dynamic triaxial test hysteresis curves. Based on the calibration results, the effects of the EPS particles volume ratio and amplitude on the contact force, displacement field, and velocity field of the lightweight soil under different accumulated strains were studied. The results showed that the hysteresis curves of lightweight soil exhibit nonlinearity, hysteresis, and strain accumulation. The strain accumulated in remolded soil is mainly tensile strain, and that in lightweight soil is mainly compressive strain. As the volume ratio of EPS particles increased, the contact force first increased and then decreased, and the displacement and velocity of the particles increased accordingly. With an increase in amplitude, the dynamic stress of the particle system increased, and the accumulation rate of the dynamic strain of the samples also increased. At 5% compressive strain, the contact force of the particles changed significantly and the number of particles deflected in the direction of velocity also increased considerably. These results indicated that the cemented structure of the lightweight soil began to fail at a compressive strain of 5%. Thus, a compressive strain of 5% is more reasonable than the dynamic strength failure standard of lightweight soil.

• Journal of Wetlands Research
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• v.18 no.2
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• pp.132-147
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• 2016

In this study the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) sensor onboard the Soil Moisture Ocean Salinity (SMOS) and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor onboard the Global Change Observation Mission-Water (GCOM-W1) based soil moisture retrievals were revised to obtain better accuracy of soil moisture and higher data acquisition rate over East Asia. These satellite-based soil moisture products are revised against a reference land model data set, called Global Land Data Assimilation System (GLDAS), using Cumulative Distribution Function (CDF) matching and regression approach. Since MIRAS sensor is perturbed by radio frequency interferences (RFI), the worst part of soil moisture retrieval, East Asia, constantly have been undergoing loss of data acquisition rate. To overcome this limitation, the threshold of RFI, DQX, and composite days were suggested to increase data acquisition rate while maintaining appropriate data quality through comparison of land surface model data set. The revised MIRAS and AMSR2 products were compared with in-situ soil moisture and land model data set. The results showed that the revising process increased correlation coefficient values of SMOS and AMSR2 averagely 27% 11% and decreased the root mean square deviation (RMSD) decreased 61% and 57% as compared to in-situ data set. In addition, when the revised products' correlation coefficient values are calculated with model data set, about 80% and 90% of pixels' correlation coefficients of SMOS and AMSR2 increased and all pixels' RMSD decreased. Through our CDF-based revising processes, we propose the way of mutual supplementation of MIRAS and AMSR2 soil moisture retrievals.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.795-806
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• 1998

Soil moisture is affected by regional climate, soil characteristics and land surface condition, etc,. Especially, the changes in land surface condition is more than other factors, which is mainly due to rapid urbanization and industrialization. This study is to evaluate how the change of land surface condition impacts on soil moisture field evolution using a simple model of soil moisture dynamics. For the quantification of soil moisture field, the first half of the paper is spared for the statistical characterization based on the first- and second-order statistics of Washita '92 and Monsoon '90 data. The second half is for evaluating the impact of land cover changes through simulation study using a model for soil moisture dynamics. The model parameters, the loss rate and the diffusion coefficient, have been estimated using the observed data statistics, where the changes of surface conditions are considered into the model by applying various parameter sets with different second-order statistics. This study is concentrated on evaluating the impact due to the changes of land surface condition variability. It is because we could easily quantify the impact of the changes of its areal mean based on the linear reservoir concept. As a result of the study, we found; (1)as the variability of land surface condition, increases, the soil moisture field dries up more easily, (2)as the variabilit y of the soil moisture field is the highest at the beginning of rainfall and decreases as time goes on to show the variability of land surface condition, (3)the diffusion effect due to surface runoff or water flow through the top soil layer is limited to a period of surface runoff and its overall impact is small compared to that of the loss rate field.

• Journal of the Korean Geotechnical Society
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• v.38 no.9
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• pp.5-17
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• 2022

Recently, several studies have been conducted on virtual fixed-point and elastic soil spring methods to simulate the soil-pile interaction in response to spectrum analysis of pile-supported structures. However, the soil spring stiffness has not been properly considered due to the seismic load magnitude, and studies on the response spectrum analysis of pile-supported structures considering this circumstance are inadequate. Therefore, in this study, the response spectrum analysis was performed considering the soil spring stiffness according to the seismic load magnitude, and the dynamic behavior of the pile-supported structure was evaluated by comparing it with existing virtual fixed-point and elastic soil spring methods. Comparing the experiment and analysis, the moment differences occurred up to 117% and 21% in the virtual fixed-point and elastic soil spring models, respectively. Moreover, when the analysis was performed using an API p-y curve considering the soil spring stiffness according to the seismic load magnitude, the moment difference between the experiment and analysis was derived at a maximum of < 4%, and it is the most accurate method to simulate the experimental model response.

• Journal of the Korean Geotechnical Society
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• v.24 no.10
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• pp.57-70
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• 2008

The advantage of piezocone penetration test is a guarantee of continuous data, which is a source of reliable interpretation of target soil layer. Many researches have been carried out f3r several decades and several classification charts have been developed to classify in-situ soil from the cone penetration test result. Since most present classification charts or methods were developed based on the data which were compiled over the world except Korea, they should be verified to be feasible for Korean soil. Furthermore, sometimes their charts provide different soil classification results according to the different input parameters. However, unfortunately, revision of those charts is quite difficult or almost impossible. In this research a new soil classification model is proposed by using fuzzy C-mean clustering and neuro-fuzzy theory based on the 5371 CPT results and soil logging results compiled from 17 local sites around Korea. Proposed neuro-fuzzy soil classification model was verified by comparing the classification results f3r new data, which were not used during learning process of neuro-fuzzy model, with real soil log. Efficiency of proposed neuro-fuzzy model was compared with other soft computing classification models and Robertson method for new data.

• Journal of Environmental Science International
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• v.23 no.11
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• pp.1827-1833
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• 2014

This study has been carried out to present the valuation system of soil carbon sequestration potentials of soil in accordance with the new climate change scenarios(RCP). For that, by analyzing variation of soil carbon of the each type of agricultural land use, it aims to develop technology to increase the amount of carbon emissions and sequestration. Among the factors which affects the estimation of determining the soil carbon model and influence power after the measurement on soil organic carbon, under the center of a causal relationship between the explanatory variables this study were investigated. Chemical fertilizers (NPK) decreased with increasing the amount of soil organic carbon and as with the first experimental results, when cultivating rice than pepper, the fact that soil organic carbon content increased has been found out. The higher the carbon dioxide concentration, the higher the amount of organic carbon in the soil and this result is reliable under a 10% significance level. On the other hand, soil organic carbon, humus carbon and hot water extractable carbon has been found out that was not affected the soils depth, sames as the result of the first year. The higher concentration of carbon dioxide, the higher carbon content of humus and hot water extractable carbon content. According to IPCC 2006 Guidelines and the new climate change scenario RCP 4.5 and the measurement results of the total amount of soil organic carbon to the crops due to abnormal climate weather, 1% increase in atmospheric carbon dioxide concentration was found to be small when compared to the growing rate of increasing 0.01058% of organic carbon in the soil.