• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.274-277
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• 2007

This study is to estimate the spatial distribution of soil loss using the land use data produced from QuickBird satellite imagery. For a small agricultural watershed (1.16 $km^2$) located in the upstream of Gyeongan-cheon watershed, a precise agricultural land use map were prepared using QuickBird satellite image of April 5 of 2003. RUSLE (Revised Universal Soil Loss Equation) was adopted for soil loss estimation. The data (DEM, soil and land use) for the RUSLE were prepared for 5 m and 30 m spatial resolution. The results were compared with each other and the result of 30 m Landsat land use data.

• Journal of Korean Society on Water Environment
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• v.25 no.1
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• pp.112-119
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• 2009

Based on the study of soil water dynamics, this study is to suggest an advanced stochastic soil water model for future study for drought application. One distinguishable remark of this study is the derivation of soil water dynamic controling equation for 3-stage loss functions in order to understand the temporal behaviour of soil water with reaction to the precipitation. In terms of modeling, a model with rather simpler structure can be applied to regenerate the key characteristics of soil water behavior, and especially the probabilistic solution of the derived soil water dynamic equation can be helpful to provide better and clearer understanding of soil water behavior. Moreover, this study will be the future cornerstone of applying to more realistic phenomenon such as drought management.

• Journal of Industrial Technology
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• v.36
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• pp.57-63
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• 2016

In this study characteristics of debris flow landslide were investigated on the focus of debris flow disaster occurred by heavy rainfall in 2013 at Goeun-ri around Kaeryoung Mt. in Chuncheon-si. Appropriate method for estimating scale of debris flow was investigated by comparing those values from soil loss by Universal Soil Loss Equation, debris flow yield rate obtained by field survey of investigating debris flow path from initiation and erosion to deposition and other methods. As results of this study, it might be an opportunity of contributing to construct the data base for determining the size of erosion control facilities in future.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.37-44
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• 2018

Universal soil loss equation (USLE) had been employed to estimate potential soil loss since it was developed from the statewide data measured and collected in the United States. The equation had an origin in average annual soil loss estimation though, it was modified or improved to provide better opportunities of soil loss estimation outside the United States. The equation has five factors, most studies modifying them to adapt regional status were focused on rainfall erosivity factor and cover management factor. While the conservation practice factor (USLE P factor) is to represent distinct features in agricultural fields, it is challenging to find studies regarding the factor improvements. Moreover, the factor is typically defined using slopes. The factor defining approach was suggested in the study, the approach is a step-by-step method allowing USLE P factor definition with given condition. The minimum condition is slope and field location to provide an opportunity for using in any GIS software and to reflect regionally distinct features. If watershed location, slope, crop type, and mulching type on furrows are given, detailed definition of the factors are possible. The approach was developed from field survey in South-Korea, it is expected to be used for potential soil loss using USLE in South-Korea.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.13-20
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• 2018

Universal Soil Loss Equation (USLE) has been widely used to estimate potential soil loss because USLE is a simple and reliable method. The rainfall erosivity factor (R factor) explains rainfall characteristics. R factors, cited in the Bulletin on the Survey of the Erosion of Topsoil of the Ministry of Environment in the Republic of Korea, are too outdated to represent current rainfall patterns in the Republic of Korea. Rainfall datasets at one minute intervals from 2013 to 2017 were collected from fifty rainfall gauge stations to update R factors considering current rainfall condition. The updated R factors in this study were compared to the previous R factors which were calculated using the data from 1973 to 1996. The coefficient of determination between the updated and the previous R factors shows 0.374, which means the correlation is not significant. Therefore, it was concluded that the previous R factors might not explain current rainfall conditions. The other remarkable result was that regression equations using annual rainfall data might be inappropriate to estimate reasonable R factors because the correlation between annual rainfall and the R factors was generally unsatisfy.

• Journal of Environmental Impact Assessment
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• v.11 no.4
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• pp.271-280
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• 2002

The purpose of this study is to explore the hydrological impacts and soil loss variation due to the land use change of Namak New Town development area. The analysis of hydrological effects and soil loss variation has been carried out using GIS in this study. In order to estimate the peak runoff volume, the Rational Method which is the most popular technique to predict runoff amounts is used. To estimate the soil loss in the study area, Universal Soil Loss Equation(USLE), which is one of the most comprehensive and useful technique to predict soil erosion is adopted. The result of this study has shown that the peak runoff volume and the total soil loss increase according to the land use change. The peak runoff volume and the total soil loss have been increased about 2 times and about 48 times more than that of pre development. The increasing of the peak runoff volume can be effective erosion, flooding and so on. A careful city planning is the first essential step to minimize the environmental impacts and to construct the ecological city.

• 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.

• Spatial Information Research
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• v.14 no.4 s.39
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• pp.363-377
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• 2006

Mean annual soil loss was calculated and critical soil erosion areas were identified for the Congaree River Basin in South Carolina, USA using the Revised Universal Soil Loss Equation (RUSLE) model. In the RUSLE model, the mean annual soil loss (A) can be calculated by multiplying rainfall-runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), crop-management (C), and support practice (P) factors. The critical soil erosion areas can be identified as the areas with soil loss amounts (A) greater than the soil loss tolerance (T) factor More than 10% of the total area was identified as a critical soil erosion area. Among seven subwatersheds within the Congaree River Basin, the urban areas of the Congaree Creek and the Gills Creek subwatersheds as well as the agricultural area of the Cedar Creek subwatershed appeared to be exposed to the risk of severe soil loss. As a prototype model for examining future effect of human and/or nature-induced changes on soil erosion, the RUSLE model customized for the area was embedded into ESRI ArcGIS ArcMap 9.0 using Visual Basic for Applications. Using the embedded model, users can modify C, LS, and P-factor values for each subwatershed by changing conditions such as land cover, canopy type, ground cover type, slope, type of agriculture, and agricultural practice types. The result mean annual soil loss and critical soil erosion areas can be compared to the ones with existing conditions and used for further soil loss management for the area.

• Journal of Korea Water Resources Association
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• v.45 no.6
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• pp.617-629
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• 2012

The land use map of the Nakdong River watershed was classified by each land use contents and analyzed to rank the risk of soil loss and erosion. Also, the soil loss and erosion was evaluated in the Nakdong River watershed using Revised Universal Soil Loss Equation (RUSLE) and the subbasin with high risk of soil loss was evaluated with the analysis results of land use contents. Finally, the analyzed results were also compared with the landslide risk map, hence the practical application methods using developed and analyzed results were considered in this study. As a result of land use analysis and RUSLE calculation, it was represented that the Naesung Stream watershed had the high risk for soil loss among the subbasins of the Nakdong River watershed. It was also presented that the high risk area identified by computation of RUSLE was corresponding to the landslide risk area. However, the high risk of soil erosion by land use near the river or wetland was confirmed only through the calculation results of RUSLE.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.5
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• pp.109-126
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• 2017

Universal soil loss equation (USLE) is used to estimate soil loss solely or employed in any hydrologic models. Since soil erosion has been an issue in South Korea for decades, the Ministry of Environment enacted a law to regulate soil erosion in 2012, which is the Notification of topsoil erosion status. The notification is composed of preliminary and field investigations, the preliminary investigation suggests to use USLE and provides USLE factors. However, the USLE factors provided in the notification was prepared at least 10 years ago, therefore it is limited to reflect recent climate changes. Moreover the current yearly USLE approach does not provide an opportunity to consider seasonal variation of soil erosion in South Korea. A GIS-based model was therefore applied to evaluate the yearly USLE approach in the notification. The GIS-based model employs USLE to estimate soil loss, providing an opportunity to estimate monthly soil loss with monthly USLE factor databases. Soil loss was compared in five watersheds, which were Geumgang, Hangang, Nakdonggang, Seomjingang, and Yeongsangang watersheds. The minimum difference was found at Seomjingang watershed, the yearly potential soil loss were 40.15 Mg/ha/yr by the notification approach and 34.42 Mg/ha/yr by the GIS-based model using monthly approach. And, the maximum difference was found at Nakdonggang watershed, the yearly potential soil loss were 27.01 Mg/ha/yr by the notification approach and 10.67 Mg/ha/yr by the GIS-based model using monthly approach. As a part of the study result, it was found that the potential soil loss can be overestimated in the notification approach.