• Korean Journal of Soil Science and Fertilizer
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• v.49 no.2
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• pp.144-156
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• 2016

Soil is a dynamic biological system, in which it is difficult to determine the composition of microbial communities. Knowledge of microbial diversity and function in soils are limited because of the taxonomic and methodological limitations associated with studying the organisms. In this review, approaches to measure microbial diversity in soil were discussed. Research on soil microbes can be categorized as structural diversity, functional diversity and genetic diversity studies, and these include cultivation based and cultivation independent methods. Cultivation independent technique to evaluate soil structural diversity include different techniques such as Phospholipid Fatty Acids (PLFA) and Fatty Acid Methyl Ester (FAME) analysis. Carbon source utilization pattern of soil microorganisms by Community Level Physiological Profiling (CLPP), catabolic responses by Substrate Induced Respiration technique (SIR) and soil microbial enzyme activities are discussed. Genetic diversity of soil microorganisms using molecular techniques such as 16S rDNA analysis Denaturing Gradient Gel Electrophoresis (DGGE) / Temperature Gradient Gel Electrophoresis (TGGE), Terminal Restriction Fragment Length Polymorphism (T-RFLP), Single Strand Conformation Polymorphism (SSCP), Restriction Fragment Length Polymorphism (RFLP) / Amplified Ribosomal DNA Restriction Analysis (ARDRA) and Ribosomal Intergenic Spacer Analysis (RISA) are also discussed. The chapter ends with a final conclusion on the advantages and disadvantages of different techniques and advances in molecular techniques to study the soil microbial diversity.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.944-958
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• 2011

Soil hydraulic properties such as hydraulic conductivity or water retention which are costly to measure can be indirectly generated by soil pedotransfer function (PTF) using easily obtainable soil data. The field soil structure description which is routinely recorded could also be used in PTF as an input to reduce the uncertainty. The purposes of this study were to use qualitative morphological soil structure descriptions and soil structural index into PTF and to evaluate their contribution in the prediction of soil hydraulic properties. We transformed categorical morphological descriptions of soil structure into quantitative values using categorical principal component analysis (CATPCA). This approach was tested with a large data set from the US National Pedon Characterization database with the aid of a categorical regression tree analysis. Six different PTFs were used to predict the saturated hydraulic conductivity and those results were averaged to quantify the uncertainty. Quantified morphological description was successively used in multiple linear regression approach to predict the averaged ensemble saturated conductivity. The selected stepwise regression model with only the transformed morphological variables and structural index as predictors predicted the $K_{sat}$ with $r^2$ = 0.48 (p = 0.018), indicating the feasibility of CATPCA approach. In a regression tree analysis, soil structure index and soil texture turned out to be important factors in the prediction of the hydraulic properties. Among structural descriptions size class turned out to be an important grouping parameter in the regression tree. Bulk density, clay content, W33 and structural index explained clusters selected by a two step clustering technique, implying the morphologically described soil structural features are closely related to soil physical as well as hydraulic properties. Although this study provided relatively new method which related soil structure description to soil structure index, the same approach should be tested using a datasets containing the actual measurement of hydraulic properties. More insight on the predictive power of soil structure index to estimate hydraulic properties would be achieved by considering measured the saturated hydraulic conductivity and the soil water retention.

• Journal of Ecology and Environment
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• v.30 no.1
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• pp.39-47
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• 2007

The relationships between the cover of herbaceous species and 15 soil chemical properties (organic carbon contents, total N, available P, exchangeable K, Na, Ca and Mg, HCl-extractable Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn) in nine poorly controlled waste landfill sites in Korea were examined by correlation analysis and multiple regression equations. Species showed different patterns of correlation between their cover values and soil chemical properties. The cover of Ambrosia artemisiifolia var. elatior, Aster subulatus var. sandwicensis and Erechtites hieracifolia were negatively correlated with the contents of Fe, Mn and Ni within landfill soils. Total cover of all species in quadrats was positively correlated with the contents of Cd and negatively correlated with the contents of Mn and Fe from stepwise regression analysis with 15 soil properties. Canonical correspondence analysis demonstrated that the distribution of native and exotic plants on poorly controlled landfills was significantly influenced by the contents of Na and Ca in soils, respectively.

• Magazine of the Korean Society of Agricultural Engineers
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• v.41 no.6
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• pp.33-43
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• 1999

Drought is a serious diaster in agriculutre, especially to upland crops. Hence, the Agricultural Drought Analysis Model (ADAM) that is integratable with GIS was applied to analyae agriculture drought in upland. ADAM is composed of two sub-models , one is a Soil Water Balance Model (SWBM) and the other is a Drougth Analysis Model (DAM) that is based on the Runs theory. The ADAM needs weather data, rainfall data and soil physical characteristics data as input and calculates daily soil moisture contents. GIS was integrated to the ADAM for the calculation of regional soil moisture using digitized landuse map, detaile dsoil map, thiessen network and district boundary . For the agriculutral drought analysis, the ADAM adapt the Runs theory for analyzing drought duration, severity and magnitude . Log-Pearson Type-III probability distribution function and Kolmogorov-Smirnov test were used to test the fitness of good of the model. The integration of ADAM with GIS was successfully implemented and would be operated effectively for the regional drought analysis.

• Current Research on Agriculture and Life Sciences
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• v.23
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• pp.53-60
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• 2005

This study was carried out in order to produce useful material for the forest multiple use and forest protection management by soil physio-chemical analysis of studied area in Mt. Namsan. The result of soil physio-chemical analysis and statical analysis represented as following. In side of physical properties of forest soil in Mt. Namsan, Soil depth was average 31.4cm and available soil depth was average 20.0cm. Soil type was Brown forest soil that representative soil type in Korea. Soil texture was sandy loom(SL) except valley area. In side of chemical properties, the range of soil acidity was 4.29 ~ 5.19 (average 4.76), organic matter content was 3.17% that compared the lowest value to organic matter content of Korea forest soil. Available phosphorus was 3.64ppm that was lower than others forest soil. Exchangeable cation content was similar to the Korea brown forest soil. Cation exchange capacity(CEC) was $8.22cmol_c/kg$ in Mt. Narnsan.

• 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.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.659-665
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• 2013

Most of dredged soil generating millions of tons per year is treated as a waste disposing in ocean or landfill except some part of recycling. The purpose of this study is to present the prerequisite for the use of dredged soil as a resource and analyse economic and environmental values of the recycling of dredged soil. The analysis of the economic and environmental value of recycling of dredged soil as a resource showed that several trillion won of budget can be saved in construction of disposal area or landfill and that loss of about 50 million tons of aggregates from deforestation can be restored by supplyment of dredged soil preserving a mountain as big as the Namsan(Mt.) every year. In order to utilize dredged soil in more diverse areas as high value of resource, the related domestic laws are needed to be readjusted integrating laws spreaded in different government departments and a special law is prepared and enacted.

• Journal of the Korean Society of Safety
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• v.20 no.1 s.69
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• pp.101-106
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• 2005

When a underground structure is constructed at the site composed of soft soil, the behavior of a underground structure Is much affected by the motion of soft soil. Therefore, the effect of soil-structure interaction is an important consideration in the design of a underground structure such as tunnel at the site composed of soft soil. This paper presents the results of the study on dynamic response of tunnel structures and soil-structure interaction effects. The computer program SASSI was used in seismic analysis of tunnel structures because it is more capable of analyzing dynamic response or structures considering soil-structure interaction. As regards the results, the flexibility of surrounding soil affects dynamic response characteristics of tunnel structures and response of tunnel structures can be amplified.

• Journal of Environmental Impact Assessment
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• v.20 no.4
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• pp.455-464
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• 2011

The purpose of this study is to clarify correlations between soil environments and the growth of trees in forests and thereon analyze effects of seasonal changes in such environments on such growth. To determine seasonal factors of soil affecting the Tree Vitality of Pinus thunbergii, first of all, the study designated the Tree Vitality as a dependent variable and soil hardness, moisture, pH, K, Na, Mg and Ca as independent variables. Then the study performed Pearson's coefficient analysis. To clarify what soil factors influence the seasonal growth of Pinus thunbergii multiple regression analysis is carried out, and findings are as follow; the growth of Pinus thunbergii was basically influenced by pH, followed by soil hardness in spring, K, followed by moisture in summer, and by soil hardness in winter. However, no soil factors affected the vitality at the significance level of 5% for t.

• 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.