• Journal of the Korean Society of Tobacco Science
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• v.22 no.2
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• pp.123-132
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• 2000

Evaluation method of soil fertility by combination of soil color characteristics and survey data from soil map as well as chemical properties was investigated on total 35 field and pot experiments. Total 35 tobacco fields including 11 fields located at Cheonweon county in Chungnam Province, 9 fields located at Goesan county in Chungbuk Province, and 15 fields located at Youngcheon county in Kyongbuk Province were selected in 1984 to cover the wide range of distribution in landscape and soil attributes. Yields of tobacco grown on the plots of both the pot and field experiment which were not applied with any fertilizer were considered as basic fertility of the soil (BFS). The BFS was estimated by 32 independent variables including 15 chemical properties, 3 color characteristics, and 14 soil survey data from soil map. Twenty-four independent variables containing 16 quantitative variables selected from 24 quantitative variables by collinearity diagnostics and 8 qualitative variables, were classified and analyzed by multiple linear regression (MLR) of REG and GLM models of SAS. Tobacco yield of field experiment showed high variations by eight times in difference between minimum and maximum yield indicating the diverse soil fertility among the experimental fields. Evaluation for the BFS by the MLR including quantitative variables was still more confidential than that by a single index and that showed more improvement of coefficient of determination ($R^2$) in pot experiment than in field experiment. Evaluation for the BFS by MLR in field experiment was still improved by adding qualitative variables as well as quantitative variables. The variability in the BFS of field experiment was explained 43.2% by quantitative variables and 67.95% by adding both the quantitative and qualitative variables compared with 21.7% by simple regression with NO$_3$-N content in soil. The regression evaluation for the best evaluation of the BFS of field experiment by MLR included NO$_3$-N content, L value, and a value of soil color as quantitative variables and available soil depth and topography as qualitative variables. 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 tobacco field.

• Journal of Forest and Environmental Science
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• v.37 no.1
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• pp.14-24
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• 2021

A plant community is a group of populations that coexist in space and interact directly or indirectly with the environment. In this paper, we determined the pattern of tree species composition in response to soil variables in Khadimnagar National Park (KNP), which is one of the least studied tropical forests in Bangladesh. Soil and vegetation data were collected from 71 sample plots. Canonical Correspondence Analysis (CCA) with associated Monte Carlo permutation tests (499 permutations) was carried out to determine the most significant soil variable and to explore the relationship between tree species distribution and soil variables. Soil pH and clay content (pH with p<0.01 and Clay content with p<0.05) were the most significant variables that influence the overall tree species distribution in KNP. Soil pH is related to the distribution and abundance of Syzygium grande and Magnolia champaca, which were mostly found and dominant species in KNP. Some species were correlated with clay content such as Artocarpus chaplasha and Cassia siamea. These observations suggest that both the physico-chemical properties of soil play a major role in shaping the tree distribution in KNP. Hence, these soil properties should take into account for any tree conservation strategy in this forest.

• Geomechanics and Engineering
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• v.23 no.5
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• pp.431-439
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• 2020

Soil-water retention curve (SWRC) contains key information for the application of unsaturated soil mechanics principles to engineering practice. The SWRC variables are commonly used to describe the hydro-mechanics of soils. Generally, these parameters are determined using the graphical method which can be time consuming. The SWRC is highly dependent on the pore size distribution (PSD). Theoretically, the PSD obtained by mercury intrusion porosimetry test can be used to determine some SWRC variables. Moreover, the relationship between SWRC and shrinkage curve has been investigated. A new method to determine total SWRC variables directly without curve-fitting procedure is proposed. Substituting the variables into linear SWRC equations construct SWRC. A good agreement was obtained between predicted and measured SWRCs, indicating the validity of the proposed method for unimodal SWRC.

• Geomechanics and Engineering
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• v.29 no.6
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• pp.599-614
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• 2022

In this study, the reliability analysis of internal and external stabilities of Reinforced Soil Walls (RSWs) under static and seismic loads are investigated so that it can help the geotechnical engineers to perform the design more realistically. The effect of various variables such as angle of internal soil friction, soil specific gravity, tensile strength of the reinforcements, base friction, surcharge load and finally horizontal earthquake acceleration are examined assuming the variables uncertainties. Also, the correlation coefficient impact between variables, sensitivity analysis, mean change, coefficient of variation and type of probability distribution function were evaluated. In this research, external stability (sliding, overturning and bearing capacity) and internal stability (tensile rupture and pull out) in both static and seismic conditions were investigated. Results of this study indicated sliding as the predominant failure mode in the external stability and reinforcing rupture in the internal stability. First-Order Reliability Method (FORM) are applied to estimate the reliability index (or failure probability) and results are validated using the Monte Carlo Simulation (MCS) method. The results showed among all variables, the internal friction angle and horizontal earthquake acceleration have dominant impact on the both reinforced soil wall internal and external stabilities limit states. Also, the type of probability distribution function affects the reliability index significantly and coefficient of variation of internal friction angle has the greatest influence in the static and seismic limits states compared to the other variables.

• Journal of Animal Science and Technology
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• v.61 no.6
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• pp.324-332
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• 2019

This study aimed to identify the causality between climatic and soil variables affecting the yield of Italian ryegrass (Lolium multiflorum Lam., IRG) in the paddy field by constructing the pathways via structure equation model. The IRG data (n = 133) was collected from the National Agricultural Cooperative Federation (1992-2013). The climatic variables were accumulated temperature, growing days and precipitation amount from the weather information system of Korea Meteorological Administration, and soil variables were effective soil depth, slope, gravel content and drainage class as soil physical properties from the soil information system of Rural Development Administration. In general, IRG cultivation by the rice-rotation system in paddy field is important and unique in East Asia because it contributes to the increase of income by cultivating IRG during agricultural off-season. As a result, the seasonal effects of accumulated temperature and growing days of autumn and next spring were evident, furthermore, autumnal temperature and spring precipitation indirectly influenced yield through spring temperature. The effect of autumnal temperature, spring temperature, spring precipitation and soil physics factors were 0.62, 0.36, 0.23, and 0.16 in order (p < 0.05). Even though the relationship between soil physical and precipitation was not significant, it does not mean there was no association. Because the soil physical variables were categorical, their effects were weakly reflected even with scale adjustment by jitter transformation. We expected that this study could contribute to increasing IRG yield by presenting the causality of climatic and soil factors and could be extended to various factors.

• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.19-26
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• 2003

An oscillating digger mechanism was designed, constructed. and tested. The mechanism is consisted of a six-bar linkage, one four-bar linkage was fer the digger blade and the other one fur variable soil-crop separation. Experimental variables were amplitude(3, 6, 9 mm). frequency(11.2, 14.9. 17.0 Hz), and forward speed of tractor(0.91, 1.13, 1.56 km/h). Each combination of these variables was replicated three times to measure the draft and torque for power requirement evaluation. and the broken-up soil height on the soil separation sieve mechanism. Four parameters λ(the ratio of vibration speed to forward velocity), p(the ratio of vibration acceleration to forward velocity), K(the ratio of vibration acceleration to gravitational acceleration), and T(the product of λ and K) were induced from three experimental variables: amplitude, frequency, and tractor speed. And the power requirement and soil separation ability were analyzed by regression. Though λ and K were known to be the representative parameters. T was the most moderate one to explain draft. torque. and soil separation in this study. It was estimated that the T equal to or greater than 2.4 was the minimum recommended value. Figure 18 would be useful fir the selection of amplitude. frequency, or operating tractor speed once any two variables are known.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.205-205
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• 2021

Surface soil moisture, which governs the partitioning of precipitation into infiltration and runoff, plays an important role in the hydrological cycle. The assimilation of satellite soil moisture retrievals into a land surface model or hydrological model has been shown to improve the predictive skill of hydrological variables. This study aims to improve streamflow prediction with Weather Research and Forecasting model-Hydrological modeling system (WRF-Hydro) by assimilating Soil Moisture Active and Passive (SMAP) data at 3 km and analyze its impacts on hydrological components. We applied Cumulative Distribution Function (CDF) technique to remove the bias of SMAP data and assimilate SMAP data (April to July 2015-2019) into WRF-Hydro by using an Ensemble Kalman Filter (EnKF) with a total 12 ensembles. Daily inflow and soil moisture estimates of major dams (Soyanggang, Chungju, Sumjin dam) of South Korea were evaluated. We investigated how hydrologic variables such as runoff, evaporation and soil moisture were better simulated with the data assimilation than without the data assimilation. The result shows that the correlation coefficient of topsoil moisture can be improved, however a change of dam inflow was not outstanding. It may attribute to the fact that soil moisture memory and the respective memory of runoff play on different time scales. These findings demonstrate that the assimilation of satellite soil moisture retrievals can improve the predictive skill of hydrological variables for a better understanding of the water cycle.

• Journal of the Korean Geographical Society
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• v.45 no.1
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• pp.95-118
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• 2010

This study aims to investigate the spatial distribution of major soil types in Korea, and to assess the ability to predict soil distribution using environmental variables. A classification tree method was used to assess soil predictability. While the great soil groups can give more intuitive understandings on their spatial distributions, its predictability using environmental factors is much lower than that of the great groups. The most important factor to determine the spatial distribution of major soil types is the geomorphological characteristic of Korea that shows distinctive morphological difference between mountains and plains. Spatial distribution of climatic variables and catenary soil sequence along slopes play additional roles in determining the distribution of soil types. The classification tree models resulted in 35-75% of prediction accuracy, depends on the combination of different environmental variables brought in the models. While geomorphological variables are the best predictors for the great groups, climatic variables perform better for the great soil groups.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.3
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• pp.160-166
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• 2009

We estimated site productivity for unstocked land based on the relationship between site index (i.e., average height of dominant trees at fixed age) and soil physico-chemical properties of Pinus densiflora stands. Site index relates to a direct method of determining a tree's response to a specific environment such as forest soil and climate conditions. We selected 78 sites in 22 P. densiflora stands of central temperate forest zone, and sampled soils for physicochemical analyzing. And 13 properties of soils were statistically treated by stepwise regression. In the degree of contribution of the variables to site index, the highly effective variables in A horizon were OM, clay content, sand content, available $P_2O_5$, and Exch. $Ca^{{+}{+}}$ inorder, and in B horizon T.N., O.M., Soil pH, cation exchange capacity(C.E.C.), and sand content in order. In both A and B horizon of the soil for P. densiflora stands, the variables commonly contributed to the site index were sand content and OM. These results may be useful to provide not only important criteria for establishment of Pinus densiflora stand sespecially in unstocked land but also aguidance for reforestation.

• Journal of the Korean Society of Tobacco Science
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• v.21 no.1
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• pp.36-48
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• 1999

Field test was conducted in Chungbuk province to evaluate the soil fertility using landscape and soil attributes by application of geographic information system(GIS) in 48 tobacco fields during 2 years(1996 ; 23 fields, 1997 ; 25 fields). The soil fertility factors and fertilizer effects were estimated by twenty five independent variables including 13 chemical properties and 12 GIS databases. Twenty five independent variables were classified by two groups, 15 quantitative indexes and 10 qualitative indexes and were analyzed by multiple linear regression (MLR) of SAS, REG and GLM models. The estimation model for evaluation of soil fertility and fertilizer effect was made by giving the estimate coefficient for each quantitative index and for each group of qualitative index significantly selected by MLR. Estimation for soil fertility factors and fertilizer effects by independent variables was better by MLR than single regression showing gradually improvement by adding chemical properties, quantitative indexes and qualitative indexes of GIS. Consequently, it is assumed that this approach by MLR with quantitative and qualitative indexes was available as an evaluation model of soil fertility and recommendation of optimum fertilization for tobacco field.