• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.09a
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• pp.86-88
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• 2002

The mathematical model was proposed to simulate ozone transport and remediation in unsaturated soils contaminated with phenanthrene. Soil column experiments were also carried out to calibrate the mathematical model. The experimental results successfully matched with the modeling results in various soil conditions. The model proposed nondimensional fraction factor to reveal reactivity between phenanthrene and gas phase ozone and liquid phase ozone. From sensitivity analysis, the fraction factor and stoichiometric coefficient decreased as water content increased. Simulation results showed increased SOM content retarded the ozone transport and the phenanthrene removal due to increased ozone consumption.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.427-436
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• 2008

This paper presents radar remote sensing of soil moisture and surface roughness for vegetated surfaces. A precise volume scattering model for a vegetated surface is derived based on the first-order radiative transfer technique. At first, the scattering mechanisms of the scattering model are analyzed for various conditions of the vegetation canopies. Then, the scattering model is simplified step by step for developing an appropriate inversion algorithm. For verifying the scattering model and the inversion algorithm, the polarimetric backscattering coefficients at 1.85 GHz, as well as the ground truth data, of a tall-grass field are measured for various soil moisture conditions. The genetic algorithm is employed in the inversion algorithm for retrieving soil moisture and surface roughness from the radar measurements. It is found that the scattering model agrees quite well with the measurements. It is also found that the retrieved soil moisture and surface roughness parameters agree well with the field-measured ground truth data.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.1
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• pp.98-106
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• 1996

An irrigation scheduling model, IRIS developed to evaluate irrigation demand and irrigation time for upland crops. For IRlS modeling the soil moisture simulation model, SWATRER was adopted and modified. The developed model, IRIS operated under 5 different soil moisture level that is 20%, 40%, 60%, 80% of available soil moisture and optimum soil moisture level, OSML, which is different about the growing stage and no rainfall condition during growing period. As a result for IRIS simulation, irrigation demand for 5 different soil moisture level was 332.3, 409.8, 569.3, 732.2, 539.3mm, irrigation number was 5, 8, 18, 54, 16 times and irrigation interval during peak time of consumptive use was 20, 13, 6, 2, 6 days respectively. It is appeared that the higher soil moisture level the more irrigation demand and irrigation number and the higher soil moisture level the less irrigation interval.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.09a
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• pp.83-86
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• 2003

Soil Aquifer Treatment (SAT) is a technique in which secondary- or tertiary-treated wastewater is infiltrated through unsaturated soil and stored in the saturated zone. In SAT, contaminants are removed by physical and biochemical reactions taking place in soils. In this study, a numerical model was developed to predict changes in water quality during SAT operations. The contaminant species considered in the model were ammonium, nitrate, dissolved organic carbon, and dissolved oxygen. The model was calibrated against experimental data obtained from one dimensional soil column tests conducted for 84 days. The calibrated model will be used to find out optimum conditions for the pilot- and regional-scale SAT operations to be scheduled for the next phase of this project.

• Structural Engineering and Mechanics
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• v.67 no.3
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• pp.267-275
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• 2018

A numerical study of soil-foundation system under monotonic and cyclic pushover loading is conducted, taking into account both material and geometric nonlinearities. A complete and refined 3D finite element (FE) model, using contact condition and allowing separation between soil and foundation, is implemented and used in order to evaluate the nonlinear relationship between applied vertical forces and induced settlements. Based on the obtained curve, a simplified model is proposed, in which the soil inelasticity is satisfactorily represented by two vertical springs with trilinear behavior law, and the foundation uplifting is insured by gap elements. Results from modeling soil-foundation system supporting a bridge pier have shown that the simplified model is able to capture irreversible settlements induced by cyclic rocking, due to soil inelasticity and vertical loading, as well as large rotations due to foundation uplifting.

• Earthquakes and Structures
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• v.22 no.4
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• pp.373-386
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• 2022

The development of performance-based design methodologies requires a reasonable definition of a displacement-response spectrum. Although ground motions are known to be significantly affected by the resonant-like amplification behavior caused by multiple wave reflections within the surface soil, such a soil-resonance effect is seldom explicitly considered in current-displacement spectral models. In this study, an analytical approach is developed for the construction of displacement-response spectra by considering the soil-resonance effect. For this purpose, a simple and rational equation is proposed for the response spectral ratio at the site fundamental period (SRTg) to represent the soil-resonance effect based on wave multiple reflection theory. In addition, a bilinear model is adopted to construct the soil displacement-response spectra. The proposed model is verified by comparing its results with those obtained from actual observations and SHAKE analyses. The results show that the proposed model can lead to very good estimations of SRTg for harmonic incident seismic waves and lead to reasonable estimations of SRTg and soil displacement-response spectra for earthquakes with a relatively large magnitude, which are generally considered for seismic design, particularly in high-seismicity regions.

• Journal of Ecology and Environment
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• v.33 no.1
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• pp.47-57
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• 2010

To understand day-to-day fluctuations in soil moisture content in Seoul, I simulated daily soil moisture content from 1908 to 2009 using long-term climatic precipitation and temperature data collected at the Surface Synoptic Meteorological Station in Seoul for the last 98 years with a hydrological simulation model, BROOK. The output data set from the BROOK model allowed me to examine day-to-day fluctuations and the severity and duration of droughts in the Seoul area. Although the soil moisture content is highly dependent on the occurrence of precipitation, the pattern of changes in daily soil moisture content was clearly quite different from that of precipitation. Generally, there were several phases in the dynamics of daily soil moisture content. The period from mid-May to late June can be categorized as the initial period of decreasing soil moisture content. With the initiation of the monsoon season in late June, soil moisture content sharply increases until mid-July. From the termination of the rainy season in mid-July, daily soil moisture content decreases again. Highly stochastic events of typhoons from late June to October bring large amount of rain to the Korean peninsula, culminating in late August, and increase the soil moisture content again from late August to early September. From early September until early October, another sharp decrease in soil moisture content was observed. The period from early October to mid-May of the next year can be categorized as a recharging period when soil moisture content shows an increasing trend. It is interesting to note that no statistically significant increase in mean annual soil moisture content in Seoul, Korea was observed over the last 98 years. By simulating daily soil moisture content, I was also able to reconstruct drought phenomena to understand the severity and duration of droughts in Seoul area. During the period from 1908 to 2009, droughts in the years 1913, 1979, 1939, and 2006 were categorized as 'severe' and those in 1988 and 1982 were categorized as 'extreme'. This information provides ecologists with further potential to interpret natural phenomenon, including tree growth and the decline of tree species in Korea.

• Korean Journal of Agricultural Science
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• v.43 no.4
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• pp.537-546
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• 2016

The development of models for agriculture systems, especially for crop production, has supported the prediction of crop yields under various environmental change scenarios and the selection of better crop species or cultivar. Crop models could be used as tools for supporting reasonable nutrient management approaches for agricultural land. This paper outlines the simplified structure of main crop models (crop growth model, crop-soil model, and crop-soil-environment model) frequently used in agricultural systems and shows diverse application of their simulated results. Crop growth models such as LINTUL, SUCROS, could provide simulated data for daily growth, potential production, and photosynthesis assimilate partitioning to various organs with different physiological stages, and for evaluating crop nutrient demand. Crop-Soil models (DSSAT, APSIM, WOFOST, QUEFTS) simulate growth, development, and yields of crops; soil processes describing nutrient uptake from root zone; and soil nutrient supply capability, e.g., mineralization/decomposition of soil organic matter. The crop model built for the DSSAT family software has limitations in spatial variability due to its simulation mechanism based on a single homogeneous field unit. To introduce well-performing crop models, the potential applications for crop-soil-environment models such as DSSAT, APSIM, or even a newly designed model, should first be compared. The parameterization of various crops under different cultivation conditions like those of intensive farming systems common in Korea, shortened crop growth period, should be considered as well as various resource inputs.

• Water Engineering Research
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• v.5 no.2
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• pp.55-68
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• 2004

The GLEAMS (Groundwater Loading Effects of Agricultural Management System, version 3.0) water quality model was used to predict hydrology and water quality and to evaluate the effects of soil types from a cattle-grazed pasture field of Bermuda-Rye grass rotation with poultry litter application as a fertilizer in North Alabama. The model was applied and evaluated by using four years (1999-2002) of field-measured data to compare the simulated results for the 2.71- ha Summerford watershed. $R^2$ values between observed and simulated runoff, sediment yields, TN, and TP were 0.91, 0.86, 0.95, and 0.69, respectively. EI (Efficiency Index) of these parameters were 0.86, 0.67, 0.70, and 0.48, respectively. The statistical parameters indicated that GLEAMS provided a reasonable estimation of the runoff, sediment yield, and nutrient losses at the studied watershed. The soil infiltration rates were compared with the rainfall events. Only high intensity rainfall events generated runoff from the watershed. The measured and predicted infiltration rates were higher during dry soil conditions than wet soil conditions. The ratio of runoff to precipitation was ranging from 2.2% to 8.8% with average of 4.3%. This shows that the project site had high infiltration and evapotranspiration which generated the low runoff. The ratio of runoff to precipitation according to soil types by the GLEAMS model appeared that Sa (Sequatchie fine sandy loam) soil type was higher and Wc (Waynesboro fine sandy loam, severely eroded rolling phase) soil type relatively lower than the weighted average of the soil types in the watershed. The model under-predicted runoff, sediment yields, TN, and TP in Wb (Waynesboro fine sandy loam, eroded undulating phase) and Wc soil types. General tendency of the predicted data was similar for all soil types. The model predicted the highest runoff in Sa soil type by 105% of the weighted average and the lowest runoff in Wc soil type by 87% of the weighted average

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.4
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• pp.51-61
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• 2002

The objective of this study is to develop GLEANS-PADDY model to predict nutrients loading from paddy-field areas. This model is developed by modifying the GLEANS model which is used for uplands, and composed of hydrology and nutrient submodels. The optimal field size for CLEANS-PADDY model application is about up to 50 ha with mild slope, relatively homogeneous Soils and spatially rainfall, and a single crop farming. The CLEAMS model is modified to handle ponded soil surface condition and saturated soil profile in paddy field. In the hydrology submodel of the CLEAMS-PADDY model. the ponded depth routing method is used to handle the ponded water condition of paddy field. To compute potential evapotranspiration the FAO-24 Corrected Blaney-Criddle method is used for paddy field instead of Penman-Monteith method in the CLEAMS model. In the nutrients submodel of the CLEAMS-PADDY model, the soil was assumed saturated and soil profile in the root zone was divided into oxidized and reduced zones.