• Korean Journal of Soil Science and Fertilizer
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• v.46 no.5
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• pp.333-342
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• 2013

Soil compaction is affected by soil texture, organic matter (OM), strength (ST) and soil moisture, which is difficult to understand the degree and effects of related factors. The purpose of the study is to assess the impact of them on the compaction with bulk density (BD). The analysis was conducted with data collected from national-wide monitoring sites including 105 upland soils, 246 orchard soils, and 408 paddy soils between 2009 and 2012. The distributions of soil physical properties were measured. The correlation and multi linear regression analysis were performed between soil physical properties using SAS. The regression equation of BD(y) includes ST, gravitational water contents (GWC), and OM as variables commonly, having additional factors, clay content and sand content in paddy soil and upland soil for only subsoil (p<0.001). Our results show that the BD could be explained about 40~50% by various physical properties. The regression was mainly determined by ST in orchard and upland soil and by the GWC in paddy soil. To mitigate soil compaction, it is important to maintain the proper level of OM in upland soil and to consider the moisture condition with soil texture in paddy soil when making work plan. Furthermore, it would be recommended the management criteria classified by soil texture for the paddy soils.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.174-179
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• 2017

Soil parameters are required inputs to crop models, which estimate crop yield under a given environment condition. The Korean Soil Information System (KSIS), which provides detailed soil profile record of 390 soil series in the HTML (HyperText Markup Language) format, would be useful to prepare soil input files. Korean Soil Information System Processing Tool (KSISPT) was developed to aid generation of soil input data based on the KSIS database. Java was used to implement the tool that consists of a set of modules for parsing the HTML document of the KSIS, storing data required for preparing soil input file, calculating additional soil parameter, and writing soil input file to a local disk. Using the automated soil data preparation tool, about 940 soil input data were created for the DSSAT model and the ORYZA 2000 model, respectively. In combination with soil series distribution map at 30m resolution, spatial analysis of crop yield could be projected under climate change, which would help the development of adaptation strategies.

• Journal of Soil and Groundwater Environment
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• v.22 no.1
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• pp.18-26
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• 2017

In a previous study, we assessed the feasibility of ferric chloride ($FeCl_3$) as a washing agent in bench-scale in-situ soil washing to remove Pb from agricultural paddy soil. Herein is a subsequent study to evaluate variations in soil properties after $FeCl_3$ soil washing in terms of fractionation and bioavailability of Pb and chemical properties of the soil. After soil washing, the soil pH decreased from 4.8 to 2.6 and the exchangeable fractions of Pb in the soil increased from 12 mg/kg to 15 mg/kg. Variations in the Pb fractionation of the soil increased Pb bioavailability by almost three-fold; however,the base saturation decreased by 75%. The concentrations of total nitrogen and available phosphate were similar before and after soil washing. The available silicate concentration significantly increased after soil washing but was two times lower than that of soil washed with HCl, which is widely used as a washing agent. This indicates that $FeCl_3$ can be an acceptable washing agent that protects the soil clay structure. The results suggest that soil amendment, such as liming, is needed to recover soil pH, reduce mobility of Pb, and provide exchangeable bases of Ca, Mg, and K as essential elements for the healthy growth of rice plants in reused soil that has been washed.

• Journal of Soil and Groundwater Environment
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• v.18 no.3
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• pp.73-81
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• 2013

Various remediation methods have been applied to clean soils contaminated with pollutants. They remove contaminants from the soils by utilizing physicochemical, biological, and thermal processes and can satisfy soil remediation standards within a limited time; however, they also have an effect on the biological functions of soils by changing soil properties. In this study, changes of the biological properties of soils before and after treatment with three frequently used remediation methods-soil washing, land farming, and thermal desorption-were monitored to investigate the effects of remediation methods on soil biological functions. Total microbial number and soil enzyme activities, germination rate and growth of Brassica juncea, biomass change of Eisenia andrei were examined the effects on soil microorganisms, plant, and soil organisms, respectively. After soil washing, the germination rate of Brassica juncea increased but the above-ground growth and total microbial number decreased. Dehydrogenase activity, germination rate and above-ground growth increased in both land farming and thermal desorption treated soil. Although the growth of Eisenia andrei in thermal desorption treated soil was higher than any other treatment, it was still lower than that in non-contaminated soil. These results show that the remediation processes used to clean contaminated soil also affect soil biological functions. To utilize the cleaned soil for healthy and more value-added purposes, soil improvement and process development are needed.

• 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.

• KIEAE Journal
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• v.10 no.3
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• pp.11-16
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• 2010

This paper has attempted to investigate the change in soil moisture volume and temperature of architecture by planting ground(soil thickness and soil mixture ratio) and ground cover plants(Sedum sarmentosum, Zoysia japonica, Chrysanthemum zawadskii) for middle region green roof system. For this, a test was conducted on the roof of Konkuk University building from April 2009 to October 2009. In terms of treatment, five types(SL, $P_7P_1L_2$, $P_6P_2L_2$, $P_5P_3L_2$, $P_4P_4L_2$) depending on soil mixture ratio and two types(15cm, 25cm) by soil depth were created. Results of soil moisture volume by soil mixture ratio in the 15cm soil thickness showed that the difference was significance between simple soil and mixture soil treatment, however, the statistical significance was not recognized according to soil mixture ratio. In case of 25cm soil thickness, soil moisture volume by soil mixture ratio was more higher 7Vol.%~10Vol.% in the mixture soil than simple soil treatment. In terms of districts planted ground cover plants, soil volume moisture differed among plants in the order Zoysia japonica 17.74 Vol.%$34.86^{\circ}C$, district non-planted $27.49^{\circ}C$, Sedum sarmentosum $25.11^{\circ}C$, Chrysanthemum zawadskii $23.08^{\circ}C$, Zoysia japonica $24.45^{\circ}C$ respectively So, concrete surface showed more higher $5^{\circ}C{\sim}15^{\circ}C$ than other things among the all the time. Result of inner temperature of the architecture and soil, it was measured inner of architecture $25.69^{\circ}C$, inner district non-planted $24.29^{\circ}C$, Chrysanthemum zawadskii $23.90^{\circ}C$, Zoysia japonica $24.02^{\circ}C$, Sedum sarmentosum $25.13^{\circ}C$, respectively.

• Journal of the Korean Institute of Landscape Architecture
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• v.33 no.2 s.109
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• pp.60-70
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• 2005

This study was carried out to elucidate the vertical characteristics of soil properties at six planted sites of land reclaimed from the sea, in Gwangyang Bay, Jeollanam-do Province, Korea. Based on the types of planting site, the chemical properties of the vertical soil layers varied. The vertical variation was great in the planting sites $Z_1\;and\;Z_2$, but less varied in the mounded planting sites $Z_3,\;Z_5,\;and\;Z_6$. Major reasons for the vertical variation in soil chemical properties included differences in the accumulation of organic matter, soil disturbance by heavy construction equipment, and heterogeneity of soil properties between soil horizons. As soil depths increased, soil salts varied. The electrical conductivity (ECe) increased in the lower areas of planting sites $Z_1\;and\;Z_2$, and the disturbed, saline planting site $Z_3$, but decreased in the lower areas of $Z_3,\;Z_5,\;and\;Z_6$. These tendencies did not coincided with exchange cation concentrations $(Na^+,\;K^+,\;Mg^{++},\;Ca^{++})$. Both total carbon (T-C) and total nitrogen (T-N) accumulated more in the lower areas of planting sites than in the higher areas, and levels were higher closer to the surface than in the soil depths. It is supposed that these tendencies are related to the accumulation of fallen leaves or other organic matter at the soil surface, and the soil chemicals then slowly move downward from the surface. Impediments to tree growth included soil hardiness, high soil salinity and exchangeable cation concentration, low soil moisture content, acidic or alkaline soil, low organic matter, heterogeneity of soil texture and establishment of soil stratification.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.1
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• pp.115-125
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• 2015

This study was carried out to analyze comparison of carbon storage and physicochemical properties of vegetation soil for extensive green rooftop established at Seoul National University in september 2013. For this study, 42 plots were made by 2 kinds of vegetation soil including A-type and B-type. A-type vegetation soil plots were made of 90% perlite and 10% humus and B-type vegetation soil plots were made of 60% perlite, 20% vermiculite, 10% coco peat and 10% humus. This study used 6 kinds of plants which are Aster koraiensis, Sedum takesimense, Zoysia japonica Steud, Euonymus japonica, Rhododendron indicum SWEET and Ligustrum obtusifolium. Field research was carried out in 11 months after planting. Physiochemical properties of B-type vegetation soil plots were better than A-type vegetation soil plots in every way and soil carbon content was also higher at B-type vegetation soil plots as well. B-type vegetation soil plots were maintained 10 to 20% higher soil water content than A-type vegetation soil plots of the study period. The species of herb which showed the best carbon storage was Zoysia japonica Steud at B-type vegetation soil plots. The species of shrub which showed the best carbon storage was Ligustrum obtusifolium at B-type vegetation soil plots. Plants generally showed better growth at B-type vegetation soil plots and B-type vegetation soil plots were higher than A-type vegetation soil plots in soil carbon stock.

• Journal of Ecology and Environment
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• v.29 no.5
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• pp.439-443
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• 2006

Soil properties of Quercus variabilis forest on Youngha valley at Mt. Worak National Park were studied as a part of Korea National Long-Term Ecological Research. Soil sampling was carried out along the 50 cm soil depth with 10cm intervals at every quarter from May 2005 through July 2006. Fresh soil was used for $NH_4{^+}-N,\;NO_3{^-}-N$, and soil water content determination. Remaining soils were air dried in the shade, and then used for determination of soil pH, T-N, T-P and exchangeable cation. Average soil organic matter in top soil was $8.5{\pm}1.2%$ and decreased with soil depth. Bulk density of top soil was $0.82{\pm}0.07g/cm^3 $and increased with soil depth. Soil organic matter and bulk density showed a negative linear correlation ($R^2=0.8464$). Soil pH in top soil and subsoil was similar. T-N, $NH_4{^+}-N,\;NO_3{^-}-N$ and T-P in top soil were $1.9{\pm}0.5mg/g,\;7.3{\pm}1.0mg/kg,\;2.0{\pm}0.4mg/kg\;and\;0.2{\pm}0.05mg/g$, respectively. $K^+,\;Ca^{2+}\;and\;Mg^{2+}$ in top soil were $84.6{\pm}24.4,\;408.8{\pm}137.8\;and\;93.4{\pm}23.0mg/kg$, respectively. They decreased with soil depth. Amounts of organic matter, T-N, $NH_4{^+}-N,\;NO_3{^-}-N$, T-P, $K^+,\;Ca^{2+}\;and\;Mg^{2+}$ in 50 cm soil depth were 250.9, 3.45, 0.025, 0.003, 0.639, 0.181, 0.845 and 0.302 ton $ha^{-1}\;50cm-depth^{-1}$, respectively.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.336-344
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• 2017

The soil water characteristics curve (SWCC) represents the relation between soil water potential and soil water content. The shape and range of SWCC according to the relation could vary depending on soil characteristics. The objective of the study was to estimate SWCC depending on soil types and layers and to analyze the trend among them. To accomplish this goal, the unsaturated three soils were considered: silty clay loam, loam, and sandy loam soils. Weighable lysimeters were used for exactly measuring soil water content and soil water potential. Two fitting models, van Genuchten and Campbell, were applied. Two models entirely fitted well the measured SWCC, indicating low RMSE and high $R^2$ values. However, the large difference between the measured and the estimated was found at the 30 cm layer of the silty clay loam soil, and the gap was wider as soil water potential increased. In addition, the non-linear decrease of soil water content according to the increase of soil water potential tended to be more distinct in the sandy loam soil and at the 10 cm layer than in the silty clay loam soil and at the lower layers. These might be seen due to the various factors such as not only pore size distribution, but also cracks by high clay content and plow pan layers by compaction. This study clearly showed difficulty in the estimation of SWCC by such kind of factors.