• Journal of Soil and Groundwater Environment
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• v.12 no.1
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• pp.64-72
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• 2007

Humans are exposed by a range of pollutants in soil via exposure routes such as ingestion, inhalation, and dermal contact. Risk assessment is a process of evaluating the adverse health effects of chemicals as a result of exposure to stressors, and it is a very useful tool to establish the cleanup goals in contaminated lands. In the exposure assessment that is one of main process in risk assessment, exposure factor plays a significant role to quantify the intake of soil pollutants. However there is a very limited study about the exposure factor applicable to Korea. In this study, we compared the exposure factors applied by the developed countries including the United States and representative European countries, and suggested the exposure factor that might be suitable in our situation. The exposure factors considered in this study include average lifetime, body weight, (exposed) skin surface area, life time, skin absorption, soil-skin adherence factor, and soil ingestion rate. This information is needed to quantitatively estimate the intake of soil pollutants in contaminated lands.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.109-125
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• 2017

This study aimed to develop a parcel-unit soil loss estimation tool embedded in Excel worksheet, USLExls, required for the design of contaminated farmland restoration project and to analyze the impact of the project carried out soil-filling work on soil loss. USLE method was adopted for the estimation of average annual soil loss in a parcel unit, and each erosivity factor in the USLE equation was defined through the review of previous studies. USLExls was implemented to allow an engineer to try out different combinations just by selecting one among the popular formulas by each factor at a combo box and to simply update parameters by using look-up tables. This study applied it to the estimation of soil loss before and after soil-filling work at Dong-a project area. The average annual soil loss after the project increased by about 2.4 times than before on average, and about 60 % of 291 parcels shifted to worse classes under the classification criteria proposed by Kwak (2005). Although average farmland steepness was lower thanks to land grading work, the soil loss increased because the inappropriate texture of the cover soil induced the soil erosion factor K to increase from 0.33 before to 0.78 after the soil-filling work. The results showed that the selection of cover soil for soil-filling work should be carefully considered in terms soil loss control and the estimation of change in soil loss should be mandatory in planning a contaminated farmland restoration project.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.4
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• pp.339-347
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• 2004

This study aims at calculating the exact soil conversion factor of cutting and banking areas of weathering rocks in large-scaled construction sites where land is being developed into home lots. For this, we have excavated the respective 20 sites of the cutting and banking areas in the said site and then calculated the volume after the excavation. As a result, the relative accuracy of the difference was calculated at 0.5% in average. We have calculated the exact soil conversion factor by the use of function ratio as per the wet unit weight and the indoor soil quality test as per volume calculated. And then we have found out minor differences as a result of the comparison and analysis with soil conversion factor determined by the dry unit weight test as per sand replacement method. This may be judged as a rational design method for the calculation of soil conversion factor, as well as high reliability of site test as a precision photogrammetry is adopted for volume measurement of the irregular excavating areas.

• Korean Journal of Soil Science and Fertilizer
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• v.35 no.6
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• pp.361-371
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• 2002

Multifunctionality of agriculture has been an important international issue in terms of environmental benefits and public concerns. We calculated soil loss mass in national basis using the USLE, and attempted to evaluate its economical benefits by replacement cost method. Soil loss mass ranged from 1.4 to $18MT\;ha^{-1}\;yr^{-1}$ was fairly fitted to measured values for 13 cropping systems. In national basis, the factors in USLE were evaluated as: 429.4 for rainfall and runoff factor. R, 0.15 for soil erodibility factor, K, 1.72 for topographic factor, LS, 0.275 for cover and management factor, C, and 0.856 for support practice factor, P. The soil loss estimated from upland farming using the USLE was $26.1MT\;ha^{-1}\;yr^{-1}$, but soil loss from the bare soil was $110.8MT\;ha^{-1}\;yr^{-1}$, the ratio of soil loss from upland farming to bare soil was 23 percents. Function of reducing soil loss in comparison with the bare soil was $84.7MT\;ha^{-1}\;yr^{-1}$, of which national soil loss mass was 62.6 million MT per annum in south Korea. Agriculture economic replacement cost of soil loss reduction was 497 billion Wons(398 million dollars) for the cost of upland soil dressing. For conservational purposes to increase the environmental benefits of upland farming, the agricultural practice including contour, strip cropping, terracing and division ditches should be implemented.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.4
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• pp.207-211
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• 2004

Evaluation of wind erodibility for the Saemangeum Reclamation Project area based on the wind erosion equation, WEQ, was attempted. Climatic factor was calculated with the climatic data for the Kunsan area, and soil erodibility factor was evaluated with the 108 soil samples collected from the project area. The soil erodibility evaluated from the non erodible aggregate percentage greater than 0.84 mm for the soil samples collected was $204.1Mg\;ha^{-1}\;yr^{-1}$ ranged from 50.08 to $642.37ha^{-1}\;yr^{-1}$. The annual climate factor based on the meteorological data in Kunsan was 3.67. The average amount of wind erosion with climate factor C from the climatic data from Kunsan and soil erodibility factor l from the soil in the project area was 7.49 Mg $ha^{-1}$ $yr^{-1}$ ranged from 1.84 Mg $ha^{-1}$ $yr^{-1}$ for silty clay loam soil to 23.57 Mg $ha^{-1}$ $yr^{-1}$ for sandy soil. The intensive wind erosion control should be needed for friable sand and loamy sand soils in the area.

• Journal of Soil and Groundwater Environment
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• v.20 no.7
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• pp.1-12
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• 2015

The purpose of this study is to highlight the National Classification System related to cleanup the soil contaminated sites and to provide some guidance to address the priority management rank system before the remediation for Busan metropolitan city. Based on the previous soil investigation data, the quantitative classification of vulnerable areas for soil pollution was performed to successfully manage the contaminated sites in Busan. Ten evaluation factors indicating the high soil pollution possibility were used for the priority management ranking system and 10 point was assigned for each factor which was evenly divided by 10 class intervals. For 16 Gu/Guns in Busan, the score of each evaluation factor was assigned according to the ratio of the area (or the number) between in each Gu (or Gun) and in Busan. Ten scores for each Gu (or Gun) was summed up to prioritize the vulnerable Gu or Guns for soil pollution in Busan. Results will be available to determine the most urgent area to cleanup in each Gu (or Gun) and also to assist the municipal government to design a successful and cost-effective site management strategy in Busan.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.405-408
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• 2002

The electrical conductivity, EC is a major indicator of soil salinity. Measuring EC of saturation-paste extract of soil, ECe, is the standard way to evaluate soil salinity. However much of the data on soil salinity have been obtained by measuring the EC of the 1:5 soil-to-water extract, EC(1:5) or salts contents(%) which multiplied by conversion factor. And, thus we attempted to collect and analysis 90 soil samples at 9 reclaimed tidelands in Korea and to derive a relationship between ECe and dilution factor at ECe and EC(1:5), $DF_{1:5}$ of 3 soil textural conditions and 6 salinity conditions. Regression equations between ECe and $DF_{1:5}$ were obtained $ECe=1.4701ln(DF_{1:5})+5.0974(r^2=0.97^{**})$ in case of more than 50% silt contents, $ECe=2.1399ln(DF_{1:5})+5.3462 (r^2=0.99^{***})$ in case of below 50% silt contents, and $ECe=1.5927ln(DF_{1:5})+5.2486 (r^2=0.98^{***})$ in all cases, and then we suggested the $DF_{1:5}\;and\;DF_%$ of 3 soil textural conditions and 6 salinity conditions.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.1043-1052
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• 2009

To derive easily the coefficient of permeability from several other soil properties, the estimation model of coefficient of permeability was proposed using linear regression analysis. The coefficient of permeability is one of the major factors to evaluate the soil characteristics. The study area is located in Kangwon-do Pyeongchang-gun Jinbu-Myeon. Soil samples of 45 spots were taken from the study area and various soil tests were carried out in laboratory. After selecting the soil factor influenced by the coefficient of permeability through the correlation analysis, the estimation model of coefficient of permeability was developed using the linear regression analysis between the selected soil factor and the coefficient of permeability from permeability test. Also, the estimation model of coefficient of permeability was compared with the results from permeability test and empirical equation, and the suitability of proposed model was proved. As the result of correlation analysis between various soil factors and the coefficient of permeability using SPSS(statistical package for the social sciences), the largest influence factor of coefficient of permeability were the effective grain size, porosity and dry unit weight. The coefficient of permeability calculated from the proposed model was similar to that resulted from permeability test. Therefore, the proposed model can be used in case of estimating the coefficient of permeability at the same soil condition like study area.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.3
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• pp.29-40
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• 2003

The objective of the paper is to compute the half-month rainfall-runoff erosivity factor for revised universal soil loss equation (RUSLE). RUSLE is being used to develop soil conservation programs and identify optimum management practices. Rainfall-runoff erosivity factor (R) is a key input parameter to RUSLE. Rainfall-runoff erosivity factor has been calculated for twenty six stations from the nationwide rainfall data from 1973 to 2002 in south Korea. The average annual Rainfall-runoff erosivity factor at the analyzed stations Is between 3,130 and 10,476 (MJ/ha)ㆍ(mm/h). According to the computation of the half-month Rainfall-runoff erosivity factor for locations, 66-85% of the average annual R value has occurred during the summer months, June-August. The half-month R values from this study can be used for RUSLE.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1586-1590
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• 2006

In order to calculate the actual erosion according to the universal soil loss equation (USLE) and to estimate the impact of land use on soil erosion in Saemangeum, it is important to know the C-factor. Based on the USLE crop-growth stages, the cover-management C-factors were calculated for the main crop and crop rotation systems by National Institute of Agricultural Science and Technology. Combining this result with statistical data about crop cultivation area and crop rotation systems, C-factors of each administrative district in Saemangeum watershed were calculated. The range of C-factors were between 0.28 and 0.35. High C-factor value was obtained with Gimje (C = 0.35) and small C-factor values were found in Wanju (C = 0.28) and Jeongeup (C = 0.29). With this result, calculated annual soil loss was 2,804,483 ton per year. Because of the lack of sufficient statistical data about crop rotation systems, further studies are required on collecting field survey data.