• Journal of Korean Society for Atmospheric Environment
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• v.19 no.5
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• pp.529-540
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• 2003

A closed chamber system was used for measuring $N_2$0 fluxes from an agriculturally managed upland soil in Kunsan during the growing season from May to July 2002. It is known that soil is one dominant source of atmospheric $N_2$O, contributing to about 57% (9 Tg y $^{-1}$ ) of the total annual global emission. Hence, its increasing emissions and concentrations are largely associated with agricultural activities. In order to elucidate characteristics of soil nitrogen emissions from intensively managed agricultural soils and to understand the roles of soil parameters (soil moisture, soil pH, soil temperature, and soil nitrogen) in the gas emission, $N_2$O soil emissions were measured at every hour during the experimental period (21 days). Soil $N_2$O fluxes were calculated based on changes of $N_2$O concentrations measured inside a closed chamber at every hour. The analysis of $N_2$O was made by using a Gas Chromatography (equipped with Electron Capture Detector). Soil parameters at sampling plots were also analyzed. Monthly averaged $N_2$O fluxes during May, June, and July were 0.14, 0.05, and 0.13 mg-$N_2$O m$^{-2}$ h$^{-1}$ , respectively. Soil temperature and soil pH did not significantly vary over the experimental period; soil temperatures ranged from 12∼$25^{\circ}C$, and soil pH ranged 4.56∼4.75. However, soil moisture varied significantly from 32% to 56% in WFPS. Relationships between soil parameters and $N_2$O fluxes exhibited positive linear relationships. Strong positive correlation ($R^2$ = 0.57, P< 0.0001) was found between $N_2$O flux and sil moisture. It suggests that soil moisture has affected strongly soil $N_2$O emissions during the experimental periods, while other parameters have remained relatively at constant levels. $N_2$O flux from agricultural soils was significant and should be taken account for the national emission inventory.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.4
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• pp.69-76
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• 2015

This paper presents the results of an investigation into the frequency-dependent electrical parameters for different types of soil as a function of moisture content. The frequency dependence of soil electrical parameters is very important in the design of grounding systems. In fact, the performance of grounding systems is greatly dependent upon various factors such as soil type, particle size, water content, temperature, frequency, and the like. The resistivity and relative permittivity for four different soils were measured and analyzed in the frequency range of 1kHz - 1MHz. Soil resistivity declined as moisture content and frequency increased. In particular, the frequency dependence of soil resistivity was significant as the moisture content was low. In contrast, the relative permittivity of soil dramatically declined at the frequency of 10kHz or below as the moisture content increased, showing the opposite pattern in terms of variation patterns, compared to resistivity.

• Magazine of the Korean Society of Agricultural Engineers
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• v.33 no.4
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• pp.61-72
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• 1991

A lumped deterministic model(DAWAST model) was developed to predict the daily streamflow. Since the streamflow is dominantly determined by the soil water storage in the watershed, the model takes the soil water accounting procedures which are based on three linear reservoirs representing the surface, unsaturated, and saturated soil layers. The variation of soil water storage in the unsaturated zone is traced from the soil water balance on a daily basis. DAWAST model consists of 5 parameters for water balance and 3 parameters for routing. A optimization technique of unconstrained nonlinear Simplex method was applied for the determination of the optimal parameters for water balance. Model verification was carried out to the 7 hydrologic watersheds with areas of 5.89-7,126km$^2$ and the results were generally satisfactory. The daily streamflow can be arbitrarily simulated with the input data of daily rainfall and pan evaporation by the DAWAST model at the station where the observed streamflow data of short periods are available to calibrate the model parameters.

• Geomechanics and Engineering
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• v.30 no.5
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• pp.437-448
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• 2022

Alluvial soil is challenging to work with due to its high compressibility. Thus, consolidation settlement of this type of soil should be accurately estimated. Accurate estimation of the consolidation settlement of alluvial soil requires accurate prediction of compressibility parameters. Geotechnical engineers usually use empirical correlations to estimate these compressibility parameters. However, no attempts have been made to develop correlations to estimate compressibility parameters of alluvial soil. Thus, this paper aims to develop new models to predict the compression and recompression indices (Cc and Cr) of alluvial soils. As part of the study, geotechnical laboratory tests have been conducted on large number of undisturbed samples of local alluvial soil. The obtained results from these tests in addition to available results from the literature from different parts in the world have been compiled to form the database of this study. This database is then employed to examine the accuracy of the available empirical correlations of the compressibility parameters and to develop the new models to estimate the compressibility parameters using the nonlinear regression analysis. The accuracy of the new models has been accessed using mean absolute error, root mean square error, mean, percentage of predictions with error range of ±20%, percentage of predictions with error range of ±30%, and coefficient of determination. It was found that the new models outperform the available correlations. Thus, these models can be used by geotechnical engineers with more confidence to predict Cc and Cr.

• Geomechanics and Engineering
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• v.33 no.6
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• pp.611-624
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• 2023

Soil properties make it attractive as a building material due to its mechanical strength, aesthetically appearance, plasticity, and low cost. However, it is frequently necessary to improve and stabilize the soil mechanical properties with binders. Soil-cement is applied for purposes ranging from housing to dams, roads and foundations. Unconfined compression strength (UCS) and split tensile strength (CD) are essential mechanical parameters for ascertaining the aptitude of soil-cement for a given application. However, quantifying these parameters requires specimen preparation, testing, and several weeks. Methodologies that allowed accurate estimation of mechanical parameters in shorter time would represent an important advance in order to ensure shorter deliverable timeline and reduce the amount of laboratory work. In this work, an extensive campaign of UCS and CD tests was carried out in a sandy soil from the Leiria region (Portugal). Then, using the machine learning tool Neural Pattern Recognition of the MATLAB software, a prediction of these two parameters based on six input parameters was made. The results, especially those obtained with resource to a Bayesian regularization-backpropagation algorithm, are frankly positive, with a forecast success percentage over 90% and very low root mean square error (RMSE).

• Magazine of the Korean Society of Agricultural Engineers
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• v.31 no.3
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• pp.57-69
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• 1989

The study was carried out for the strength parameter of coarse grained Soil and slope stability analysis of earth dam. The test samples were taken fifteen kinds of soil from cohesive soil to coarse gravel. The degree of compaction of test samples for shear test and permeability test was chosen 95 percentage of maximum dry density. The results of this study are as follows ; 1.The maximum dry density(Yd) of coarse grained soil increase in proportion to coarse particles(P) with the relation of Y d= 1.609+0.0043P. 2.The coefficients of permeability(k) decrease by the increase of fine particles(n) with the relation of k=0.0426e-0 185n. 3.The cohesions of soil decrease by the increase of coarse particles, but internal friction angles are more increased in same condition. 4.The internal friction angles(${\Phi}$) decrease in inverse proportion to void ratio(e) with the relation of ${\Phi}$ = 73.068 - 69.268e. 5.The strength parameters( Ct ${\Phi}$t) by triaxial compression test are clearly smaller than that (Cd, ${\Phi}$d) by direct shear test in fine grained soil, but the differences between both parameters are a little in coarse grained soil.The relations of both parameters are as follows; Ct = O.544Cd + 0.04 ${\Phi}$t= 1.282${\Phi}$d-2306 6.In cohesive soil, the strength parameters( Cl ${\Phi}$l) by large size shear test apparatus are similar to the strength parameters(Cs , ${\Phi}$s) by small size shear test appratus, but Cs and ${\Phi}$s values are larger than Cl and ${\Phi}$l values from 10 percentage to 20 percentage in coarse grained soil. 7.The fine grained soil is inappropriate to high dam more than 20 meters and it must be taken coarse grained soil with high internal friction angle for high dam.

• Water Engineering Research
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• v.5 no.3
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• pp.133-146
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• 2004

Soil and water assessment tool (SWAT) was simulated based on the default parameters and a priori soil parameter estimation method in Bocheong watershed of Korea. The performance of the model was tested against the measured daily runoff data for 5 years between 1993 and 1997. The sensitivity analysis of SWAT model parameters was conducted to identify the most sensitive model parameters affecting the model output. The results of SWAT simulation indicate that the overall performance of SWAT in calculating daily runoff is reasonably acceptable. However, there is a problem in estimating the low flow components of streamflow since the low flow components simulated by SWAT are significantly different from the measured low flow. The sensitivity analysis with SWAT points out that soil related parameters are the most sensitive parameters affecting surface and ground water balance components and groundwater flow related parameters exhibit negligible sensitivity.

• Geomechanics and Engineering
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• v.38 no.3
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• pp.231-247
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• 2024

The use of lime stabilization and geosynthetic reinforcement is a common approach to improve the performance of fine-grained soils in geotechnical applications. However, the impact of this combination on the soil-geosynthetic interaction remains unclear. This study addresses this gap by evaluating the interface efficiency and soil-geosynthetic interaction parameters of lime-stabilized clay (2%, 4%, 6%, and 8% lime content) reinforced with geotextile or geogrid using direct shear tests at various curing times (1, 7, 14, and 28 days). Additionally, machine learning algorithms (Support Vector Machine and Artificial Neural Network) were employed to predict soil shear strength. Findings revealed that lime stabilization significantly increased soil shear strength and interaction parameters, particularly at the optimal lime content (4%). Notably, stabilization improved the performance of soil-geogrid interfaces but had an adverse effect on soil-geotextile interfaces. Furthermore, machine learning algorithms effectively predicted soil shear strength, with sensitivity analysis highlighting lime percentage and geosynthetic type as the most significant influencing factors.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.771-776
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• 1999

RUSLE was applied to estimate annual soil loss from two small agricultural watersheds in Kangwon-do, Korea. GIS input parameters were prepared by using DEMs and soil maps prepared by the NGIS project and Rural Development Adminstration, respoctively. RUSLE parameters were prepared based on existing data and equations. Estimated annual soil loss was graphically presented to easily visualize the large soil loss area. Uplands and vineyards proved to be the two greatest sources for soil erosion. It was suggested to develop effective management practices to reduce the soil erosion from uplands and vineyards.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.57-66
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• 2016

Harmonized World Soil Database (HWSD) including the global soil information has been implemented to the runoff analysis in many watersheds of the world. However, its accuracy can be a critical issue in the modeling because of the limitation the low resolution reflecting the physical properties of soil in a watershed. Accordingly, this study attempted to assess the effect of HWSD in modeling by comparing parameters of the rainfall-runoff model using HWSD with the detailed soil map. For this, Grid based Rainfall-runoff Model (GRM) was employed in the Hyangseok watershed. The results showed that both of two soil maps in the rainfall-runoff model are able to well capture the observed runoff. However, compared with the detailed soil map, HWSD produced more uncertainty in the GRM parameters related to soil depth and hydraulic conductivity during the calibrations than the detailed soil map. Therefore, the uncertainty from the limited information on soil texture in HWSD should be considered for better calibration of a rainfall-runoff model.