• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.241-246
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• 2005

Doam watershed is located at alpine areas in the Kangwon province. The annual average precipitation, including snow accumulation during the winter, at the Doam watershed is significantly higher than other areas. Thus, pollutant laden runoff and sediment discharge from the alpine agricultural fields are causing water quality degradation at the Doam watershed. To estimate soil erosion from the agricultural fields, the Universal Soil Loss Equation (USLE) has been widely used because of its simplicity to use. The USLE rainfall erosivity (R) factor is responsible for impacts of rainfall on soil erosion. Thus, use of constant R factor for the Doam watershed cannot reflect variations in precipitation patterns, consequently soil erosion estimation. In the early spring at the Doam watershed, the stream flow increases because of snow melt, which results in erosion of loosened soil experiencing freezing and thaw during the winter. However, the USLE model cannot consider the impacts on soil erosion of freezing and thaw of the soil. Also, it cannot simulate temporal changes in USLE input parameters. Thus, the Soil and Water Assessment Tool (SWAT) model was investigated for its applicability to estimate soil erosion at the Doam watershed, instead of the widely used USLE model. The SWAT hydrology and erosion/sediment components were validated after calibration of the hydrologic component. The $R^2$ and Nash-Sutcliffe coefficient values are higher enough, thus it was found the SWAT model can be efficiently used to simulate hydrology and sediment yield at the Doam watershed. The effects of snow melt on SWAT estimated stream flow and sediment were investigated using long-term precipitation and temperature data at the Doam watershed. It was found significant amount of flow and sediment in the spring are contributed by melting snow accumulated during the winter. Thus, it is recommend that the SWAT model capable of simulating snow melt and long-term weather data needs to be used in estimating soil erosion at alpine agricultural land instead of the USLE model for successful soil erosion management at the Doam watershed.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.7
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• pp.3-12
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• 2004

The need to predict the rate of soil erosion, both under existing conditions and those expected to occur following soil conservation practice, has been led to the development of various models. In this study Morgan model especially developed for field-sized areas on hill slopes was applied to assess the rate of soil erosion using RS/GIS environment in the Dukchun river basin, one of two tributaries flowing into Jinyang lake. In order to run the model, land cover mapping was made by the supervised classification method with Landsat TM satellite image data, the digital soil map was generated from scanning and screen digitizing from the hard copy of soil maps, digital elevation map (DEM) in order to generate the slope map was made by the digital map (DM) produced by National Geographic Information Institute (NGII). Almost all model parameters were generated to the multiple raster data layers, and the map calculation was made by the raster based GIS software, IL WIS which was developed by ITC, the Netherlands. Model results show that the annual soil loss rates are 5.2, 18.4, 30.3, 58.2 and 60.2 ton/ha/year in forest, paddy fields, built-up area, bare soil, and upland fields respectively. The estimated rates seemed to be high under the normal climatic conditions because of exaggerated land slopes due to DEM generation using 100 m contour interval. However, the results were worthwhile to estimate soil loss in hilly areas and the more precise result could be expected when the more accurate slope data is available.

• Journal of Wetlands Research
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• v.14 no.3
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• pp.317-328
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• 2012

The objects of this study are to perform appropriateness analysis of USLE(universal soil loss equation) model and to accumulate the data measured in field. The basin area of Bongdong station is $342.27km^2$. This study simulated sediment outflows in the basin and performed a comparative analysis of simulated outputs with actual measurement values. Also annual rainfall was used to calculate rainfall-runoff erosivity factor which can influence soil erosion. The calculation of annual average soil erosion was made by soil erosion maps. The maps with a resolution of ($30m{\times}30m$) were created by multiplication of factors(R, LS, K, C, P) from ArcView Map Calculator. In this paper, it was shown that soil erosion was not occur in the most of basin.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.4
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• pp.24-36
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• 2003

This study integrates the revised universal soil loss equation(RUSLE) with a grid-based GIS method to assess the potential risk of soil erosion at the watershed scale. Data used in this study to generate the RUSLE factors include several thematic maps such as land use, topographic and soil maps, together with tabular precipitation data. Based on the RUSLE estimation for all the grids(10m cells) in the corresponding watershed, a cumulative histogram for the annual soil loss can be constructed. As the results, it shows that the 83.5% value of the annual soil loss for the watershed is less than 1ton/ha. However, the above 30% of agricultural land is defined as a medium or very high-risk area(more than 10ton/ha/yr). So it is necessary to establish soil conservation practices to reduce soil erosion based on the field observations.

• Journal of Korean Society on Water Environment
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• v.23 no.5
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• pp.650-658
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• 2007

The Universal Soil Loss Equation (USLE) has been used in over 100 countries to estimate potential long-term soil erosion from the field. However, the USLE estimated soil erosion cannot be used to estimate the sediment delivered to the stream networks. For an effective erosion control, it is necessary to compute sediment delivery ratio (SDR) for watershed and sediment yield at watershed outlet. Thus, the Sediment Assessment Tool for Effective Erosion Control (SATEEC) was developed to compute the sediment yield at any point in watershed. In this study, the SATEEC was applied to the Sudong watershed, Chuncheon Gangwon to compare the sediment yield using area-based sediment delivery ratio (SDRA) and slope-based sediment delivery ratio (SDRS) at watershed outlet. The sediment yield using the SDRA by Vanoni, SYA and the sediment yield using the SDRS by Willams and Berndt, SYS were compared for the same sized watersheds. The 19 subwatersheds was 2.19 ha in size, the soil loss and sediment yield were estimated for each subwatershed. Average slope of main stream was about 0.86~3.17%. Soil loss and sediment yield using SDRA and SDRS were distinguished depending on topography, especially in steep and flat areas. The SDRA for all subwatersheds was 0.762, however the SDRS were estimated in the range of 0.553~0.999. The difference between SYA and SYS was -79.74~27.45%. Thus site specific slope-based SDR is more effective in sediment yield estimation than area-based SDR. However it is recommended that watershed characteristic need to be considered in estimating yield behaviors.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.188-188
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• 2016

The Mekong which is one of the world's most significant rivers plays an extremely important role to South East Asia. Lying across six riparian countries including China, Myanmar, Thailand, Laos, Cambodia and Vietnam and being a greatly biological and ecological diversity of fishes, the river supports a huge population who living along Mekong Basin River. Therefore, much attention has been focused on the giant Mekong Basin River, particularly, the soil erosion and sedimentation problems which rise critical impacts on irrigation, agriculture, navigation, fisheries and aquatic ecosystem. In fact, there have been many methods to calculate these problems; however, in the case of Mekong, the available data have significant limitations because of large area (about 795 00 km2) and a failure by management agencies to analyze and publish of developing countries in Mekong Basin River. As a result, the Universal Soil Loss Equation (USLE) model in a GIS (Geographic Information System) framework was applied in this study. The USLE factors contain the rainfall erosivity, soil erodibility, slope length, steepness, crop management and conservation practices which are represented by raster layers in GIS environment. In the final step, these factors were multiplied together to estimate the soil erosion rate in the study area by using spatial analyst tool in the ArcGIS 10.2 software. The spatial distribution of soil loss result will be used to support river basin management to find the subtainable management practices by showing the position and amount of soil erosion and sediment load in the dangerous areas during the selected 56- year period from 1952 to 2007.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.5
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• pp.85-96
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• 2003

The Revised Universal Soil Loss Equation (RUSLE) has been used in over 100 countries to estimate potential long-term soil erosion from the field. However, the RUSLE estimated soil erosion cannot be used to estimate the sediment delivered to the stream networks. For an effective erosion control, it is necessary to compute sediment delivery ratio (SDR) for watershed and sediment yield at watershed outlet. Thus, the Sediment Assessment Tool for Effective Erosion Control (SATEEC) was developed in this study to compute the sediment yield at any point in the watershed. To compute spatially distributed sediment yield map, the RUSLE was first integrated with the ArcView GIS and three area based sediment delivery ratio methods were incorporated in the SATEEC. The SATEEC was applied to the Bangdong watershed, Chuncheon, Gangwon Province to demonstrate how it can be used to estimate soil loss and sediment yield for a watershed. The sediment yield using USDA SDR method is 8,544 ton/year and 4,949 ton/year with the method by Boyce. Thus, use of watershed specific SDR is highly recommended when comparing the estimated sediment yield with the measured sediment data. The SATEEC was applied with hypothetical cropping scenario and it was found that the SATEEC can be used to assess the impacts of different management on the sediment delivered to the stream networks and to find the sediment source areas for a reach of interest. The SATEEC is an efficient tool to find the best erosion control practices with its easy-to-use interface.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.179-190
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• 2018

The purpose of this study is an analysis of the risk of soil erosion before and after the maintenance of riparian area using the Revised Universal Soil Loss Equation (RUSLE) model based on GIS and digitizing data. To analysis of soil erosion loss in the study area, land cover maps, topographical maps, soil maps, precipitation and other data were used. After digitizing the riparian area of the Geumhogang, the area is divided into administrative district units, respectively. Amount of soil loss was classified into 5 class according to the degree of loss. Totally, 1 and 5 class were decreased, and 2-4 class were increased. Daegu and Yeongcheon decreased the area of 5 class, and Gyeongsan did not have area of 5 class. The reason for this is thought to be the decrease of the 5 class area due to the park construction, expansion of artificial facilities, and reduction of agricultural land. Simplification of riverside for river dredging and park construction has increased the flow rate of the riverside and it is considered that the amount of soil erosion has increased.

• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.66-73
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• 2017

Empirical erosion models like Universal Soil Loss Equation (USLE) models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well utilizing big data related to climate, geography, geology, land use, etc within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models are still powerful tools to distinguish the erosion-prone areas at large scale, but physics-based models are necessary to better analyze soil erosion and deposition as well as the eroded particle transport. In this study a physics-based soil erosion modeling system was developed to produce both runoff and sediment yield time series at watershed scale and reflect them in the erosion and deposition maps. The developed modeling system consists of 3 sub-systems: rainfall pre-processor, geography pre-processor, and main modeling processor. For modeling system validation, we applied the system for various erosion cases, in particular, rainfall-runoff-sediment yield simulation and estimation of probable maximum sediment (PMS) correlated with probable maximum rainfall (PMP). The system provided acceptable performances of both applications.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.19-27
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• 2012

RUSLE(Revised Universal Soil Loss Equation) has been widely used to estimate the soil loss amount of watersheds from rainfall erosivity, soil erodibility, topographic features and cropping management condition. Rainfall erosivity is the most dominant and sensitive factor among these so that the determination of reliable rainfall erosivity is essential to estimate the soil loss of watershed. Since there has been no criterion to determine the rainfall erosivity in Korea, the empirical values, determined from the relation between the annual average rainfall and erosivity or suggested by TBR(Transport Research Board), have been used for designing the erosion control structure and controlling the soil erosion for watersheds. In this study, the procedure for estimating the rainfall erosivity using frequency analysis is proposed. The most fitted distribution function, with calculated rainfall erosivities with various frequencies and durations, has been also selected. The suggested procedure can be used to estimate the optimal value of rainfall erosivity for RUSLE in order to design soil erosion structures and control the soil erosion in watersheds effectively.