• Journal of Soil and Groundwater Environment
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• v.23 no.1
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• pp.14-24
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• 2018

In soil washing, there are many variables including types of reagent and contaminant, washing time, soil-liquid ratio, washing cycles, washing agent concentrations, and etc. To identify the most influencing factors on soil washing process, regression analysis was performed for eight single variables and five combined variables. A quantitative model that employs W/H (molar ratio of washing agent to heavy metal) as a major variable was established based on the regression. The validity of the model was demonstrated by conducting lab experiments with Cu, Pb, Zn, Ni and As-contaminated soils, and various washing reagents including acetic acid, citric acid, malic acid, oxalic acid, ethylenediamine tetraacetic acid (EDTA) and nitriloacetic acid (NTA). The washing efficiencies were compared with the EDTA washing data reported in the literature. The correlation between W/H and removal efficiency was analyzed after dividing data into two groups according to the heavy metal mobility.

• Journal of Animal Science and Technology
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• v.63 no.2
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• pp.339-353
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• 2021

This study aimed to assess the causality of different climate variables on the production of whole crop maize (Zea mays L.; WCM) in the central inland region of the Korea. Furthermore, the effect of these climate variables was also determined by looking at direct and indirect pathways during the stages before and after silking. The WCM metadata (n = 640) were collected from the Rural Development Administration's reports of new variety adaptability from 1985-2011 (27 years). The climate data was collected based on year and location from the Korean Meteorology Administration's weather information system. Causality, in this study, was defined by various cause-and-effect relationships between climatic factors, such as temperature, rainfall amount, sunshine duration, wind speed and relative humidity in the seeding to silking stage and the silking to harvesting stage. All climate variables except wind speed were different before and after the silking stage, which indicates the silking occurred during the period when the Korean season changed from spring to summer. Therefore, the structure of causality was constructed by taking account of the climate variables that were divided by the silking stage. In particular, the indirect effect of rainfall through the appropriate temperature range was different before and after the silking stage. The damage caused by heat-humidity was having effect before the silking stage while the damage caused by night-heat was not affecting WCM production. There was a large variation in soil surface temperature and rainfall before and after the silking stage. Over 350 mm of rainfall affected dry matter yield (DMY) when soil surface temperatures were less than 22℃ before the silking stage. Over 900 mm of rainfall also affected DMY when soil surface temperatures were over 27℃ after the silking stage. For the longitudinal effects of soil surface temperature and rainfall amount, less than 22℃ soil surface temperature and over 300 mm of rainfall before the silking stage affected yield through over 26℃ soil surface temperature and less than 900 mm rainfall after the silking stage, respectively.

• Journal of Biosystems Engineering
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• v.25 no.6
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• pp.497-502
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• 2000

For the analysis of geothermal energy utilization in agriculture the relations between soil temperature and geographical variables such as latitude longitude and sea level in Korea were analyzed and the regression equations were suggested among them. The measured soil temperature data for four years in eighteen cities were used to get the soil temperature fitting equation depending on the soil depth and the time of year in each city. The mean correlation coefficient for those data fitting was 0.980. the correlation coefficient of regression analysis for the mean soil temperature($T_{m}$) on the geographical variables such as latitude longitude and height above sea level was 0.958 and those for soil surface temperature amplitude(Tss) and phase constant(tp) were 0.889, 0.835, respectively. The relation between the apparent thermal diffusivity of the soil and the three geographical variables was not significant. The regression equations for the mean soil temperature($T_{m}$) soil surface temperature amplitude(Tss) and phase constant(tp) adopting latitude($X_{1}$) longitude($X_2$) height above sea level($X_3$) were as follows : $T_{m}$=50.049 - $0.849X_1$-$0.03131X_2$-$0.00622X_3$Tss=-6.970 +$0.584X_1$+$0.00530X_2$-$0.00214X_3$tp=70.353 - $1.404X_1$+ $0.02098X_2$+ $0.00312X_3$

• Journal of Korean Society of Forest Science
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• v.79 no.1
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• pp.16-20
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• 1990

Canonical correlation analysis was used to relate 17 soil-site variables to bamboo diameter, height, and internodal characteristics. The first canonical correlation was highly significant, explained much of the variance in both sets of variables, and the canonical variates made sense biologically. Surface soil depth, total nitrogen and percent organic matter had high positive correlations with the first soil-site canonical variate. Clay content (%) and cation exchange capacity were negatively correlated with the first soil-site canonical variate. Only 8 of predictor variables were considered relevant for predicting bamboo growth.

• Korean Journal of Soil Science and Fertilizer
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• v.33 no.4
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• pp.221-233
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• 2000

Evaluation method of soil fertility by application of geographic information system (GIS) which includes landscape characteristics and soil map data was investigated from productivities of red pepper and tobacco grown on the fields with no fertilization. Total 131 fields experiments, 64 fields of red pepper and 67 fields of tobacco were conducted from 22 and 23 fields for red pepper and tobacco, respectively, located at Cheangweon and Eumseong counties in 1996, from 20 and 25 fields at Boeun and Goesan counties in 1997, and 22 and 19 fields at Jincheon and Chungju counties in 1998. All the experimental sites were selected on the basis of wide range of distribution in landscape and soil attributes. Dry weights and nutrients (N, P and K) uptakes by red pepper plant and tobacco leaves were considered as basic fertility of the soil (BFS). The BFS was estimated by twenty-five independent variables including 13 chemical properties and 12 GIS data. Twenty-five independent variables were classified by two groups, 15 quantitative variables and 10 qualitative variables, and were analyzed by multiple linear regression (MLR) of REG and GLM models of SAS. Dry weight of red pepper (DWRP) and dry weight of tobacco leaves (DWTL) every year showed high variations by five times in difference plots with minimum yield and maximum yield indicating the diverse soil fertility among the experimental fields. Evaluation for the BFS by the MLR including independent variables was better than that by simple regression showing gradual improvement by adding chemical properties, quantitative variables, and qualitative variables of the GIS. However the evaluation for the BFS by the MLR showed the better result for tobacco than red pepper. For example the variability in the DWTL by MLR was explained 34.2% by only chemical properties, 35.0% by adding quantitative variables, and 72.5% by adding both the quantitative and qualitative variables of the GIS compared with 21.7% by simple regression with $NO_3-N$ content in soil. Consequently, it is assumed that this approach by the MLR including both the quantitative and qualitative variables was available as an evaluation model of soil fertility for upland field.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.1
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• pp.47-55
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• 2021

The objective of this study was to access the effect of climate and soil factors on alfalfa dry matter yield (DMY) by the contribution through constructing the yield prediction model in a general linear model considering climate and soil physical variables. The processes of constructing the yield prediction model for alfalfa was performed in sequence of data collection of alfalfa yield, meteorological and soil, preparation, statistical analysis, and model construction. The alfalfa yield prediction model used a multiple regression analysis to select the climate variables which are quantitative data and a general linear model considering the selected climate variables and soil physical variables which are qualitative data. As a result, the growth degree days(GDD) and growing days(GD), and the clay content(CC) were selected as the climate and soil physical variables that affect alfalfa DMY, respectively. The contributions of climate and soil factors affecting alfalfa DMY were 32% (GDD, 21%, GD 11%) and 63%, respectively. Therefore, this study indicates that the soil factor more contributes to alfalfa DMY than climate factor. However, for examming the correct contribution, the factors such as other climate and soil factors, and the cultivation technology factors which were not treated in this study should be considered as a factor in the model for future study.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.748-754
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• 2010

The contents of soil organic matter (SOM) and $Al_o+1/2Fe_o$ in soils are important criteria for the classification of new Andisols in Soil Taxonomy system. There are many soil types in Jeju Island with various soil forming environments. This paper was conducted to estimate the contents of soil organic matter and the content of ammonium oxalate extracted Al and Fe ($Al_o+1/2Fe_o$) using various environmental variables and to make soil property maps using a statistical analyses. The soil samples were collected from 321 locations and analyzed to measure the contents of SOM and $Al_o+1/2Fe_o$. It was analyzed the relationships among them and various environmental variables such as temperature, precipitation, net primary product, radiation, evapotranspiration, altitude, soil forming energy, topographic wetness index, elevation, difference surrounded area, and distances from the shore and the peak. We can exclude multi-collinearity among environmental variables with principal component analysis and reduce all the variables to 3 principal components. The contents of SOM and $Al_o+1/2Fe_o$ were estimated by multiple regression models and maps of them were made using the models.

• Journal of Forest and Environmental Science
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• v.31 no.3
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• pp.177-191
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• 2015

The effect of environmental variables on the presence and abundance of tree species in a tropical lowland undisturbed limestone and non-limestone forest in Ben En National Park, Vietnam was investigated. The relationships between 13 environmental variables and 29 tree species with a DBH ${\geq}10cm$, as well as between six 6 physical variables with 26 species of seedling and sapling communities were assessed by canonical correspondence analysis (CCA). Data concerning all tree species ${\geq}10cm$ DBH were collected from eighteen $400m^2$ sample plots, while the abundance of regeneration (all individuals ${\leq}5cm$ DBH) was counted in fifty $2{\times}20m$ strip-plots. The significance of species-environments correlations were tested by distribution-free Monte Carlo tests. The CCA of the 29 examined tree species and 13 environmental variables indicated that the presence and abundance of the tree species were closely related to topographic factors. We may confirm that soil properties including pH, soil moisture content, and soil textures, were the most crucial factor in tree species composition and their distribution. Several species including Pometia pinnata, Amesiodendron chinense, Gironniera cuspidate, Cinnamomum mairei, and Caryodaphnopsis tonkinensis were not controlled by soil properties and topographic variables. The CCA also indicated that the abundance of regeneration tree species at all sites had positive and significant correlations with soil depth, while the occurrence of several other tree species (such as Koilodepas longifolium and Aglaia dasyclada) was positively correlated with a higher slope and rocky outcrop.

• Geomechanics and Engineering
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• v.33 no.1
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• pp.77-89
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• 2023

This study aims to establish the correlations between variables related to a slope during rainfall and factor of safety (FOS) and displacement using a coupling analysis method that is designed to consider both in rainfall conditions. With the recent development of measurement technologies, the approach of using the measurement data in the field has become easier. Particularly, they have been obtained in tests to determine the real-time safety and movement of a slope; however, a specific method has not been finalized. In addition, collected measurement data for recognizing the FOS and displacement in real-time with a specific relevance is difficult, and risks of uncertainty, such as in soil parameters and time, exist. In this study, the correlations between various slope-related variables (i.e., rainfall intensity, rainfall duration, angle of the slope, and mechanical properties including strength parameters of selected three types of soil; loamy sand, silt loam, sand) and the FOS and displacement are analyzed in order of seepage analysis, slope stability analysis and slope displacement analysis. Moreover, the methodology of coupling analysis is verified and a fundamental understanding of the factors that need to be considered in real-time observations is gained. The results show that the contributions of the abovementioned variables vary according to the soil type. Thus, the tendency of the displacement also differs by the soil type and variables but not same tendency with FOS. The friction angle and cohesion are negative while the rainfall duration and rainfall intensity are positive with the displacement. This suggests that understanding their correlations is necessary to determine the safety of a slope in real-time using displacement data. Additionally, databases considering rainfall conditions and a wide range of soil characteristics, including hydraulic and mechanical parameters, should be accumulated.

• Geomechanics and Engineering
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• v.34 no.6
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• pp.597-609
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• 2023

One of the applicable methods for the stabilization of soil walls is the nailing system which consists of tensile struts. The stability and safety of soil nail wall systems are influenced by the geometrical parameters of the nailing system. Generally, the determination of nailing parameters in order to achieve optimal performance of the nailing system for the safety of soil walls is defined in the framework of optimization problems. Also, according to the various uncertainty in the mechanical parameters of soil structures, it is necessary to evaluate the reliability of the system as a probabilistic problem. In this paper, the optimal design of the nailing system is carried out in deterministic and probabilistic cases using meta-heuristic and reliability-based design optimization methods. The colliding body optimization algorithm and first-order reliability method are used for optimization and reliability analysis problems, respectively. The objective function is defined based on the total cost of nails and safety factors and reliability index are selected as constraints. The mechanical properties of the nailing system are selected as design variables and the mechanical properties of the soil are selected as random variables. The results show that the reliability of the optimally designed soil nail system is very sensitive to uncertainty in soil mechanical parameters. Also, the design results are affected by uncertainties in soil mechanical parameters due to the values of safety factors. Reliability-based design optimization results show that a nailing system can be designed for the expected level of reliability and failure probability.