• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.357-360
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• 2005

Soil loss is widely recognized as a threat to farm livelihoods and ecosystem integrity worldwide. Soil loss prediction models can help address long-range land management planning under natural and agricultural conditions. Even though it is hard to find a model that considers all forms of erosion, some models were developed specifically to aid conservation planners in identifying areas where introducing soil conservation measures will have the most impact on reducing soil loss. Revised Universal Soil Loss Equation (RUSLE) computes the average annual erosion expected on hillslopes by multiplying several factors together: rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C), and support practice (P). The value of these factors is determined from field and laboratory experiments. This study calculated soil erosion using GIS-based RUSLE model in Imha basin and examined soil erosion source area using SPOT 5 high-resolution satellite image and land cover map. As a result of analysis, dry field showed high-density soil erosion area and we could easily investigate source area using satellite image. Also we could examine the suitability of soil erosion area applying field survey method in common areas (dry field & orchard area) that are difficult to confirm soil erosion source area using satellite image.

• Journal of Korean Society of Rural Planning
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• v.11 no.2 s.27
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• pp.9-19
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• 2005

The purpose of this study is to analyze the potential soil loss and hazard zone by the Revised Universal Soil Loss Equation(RUSLE) for preservation and management of land resources which is the base of ecosystem, and to grasp the relationship between RUSLE factors in the Nakdong River Basin. All thematic maps used in RUSLE are constructed through GIS and spatial analysis method derived from digital topographic maps, detailed soil maps, land-cover maps, and mean annual precipitation of 30 years collected respectively from National Geographic Information Institute, National Institute of Agricultural Science and Technology, and Ministry of Environment. The slope length of LS-factor that takes much times by the study area's wideness was calculated automatically through AML(Arc Macro Language) program developed by Van Remortel et al.(2001, 2003). The results are as follows; First, according to the soil loss estimation by the RUSLE, it shows that approximately 82% of the study area have relatively lower possibility of soil loss which is the 1 ton/ha in annual soil loss. While, 9.4% ($2,228km^2$) needed intensive and continuous management for soil loss. Because the amount of their annual soil loss was greater than 10 ton/ha that is optimum level suggested by Morgan(1995). For these areas, the author believe that a new approach which can minimize environmental impacts from soil loss through improvement of cultivation process and buffer forest zone should be applied. Second, according to the relationship between the RUSLE factors, topographical(LS-factor) and cover management(C-factor) conditions have a lot of influence on soil loss in case of the Nakdong River Basin. However, because of RUSLE factor's influence that affect to soil loss might be different based on the variety of spatial hierarchy and extent, it is necessary to analyze and evaluate factor's relationship in terms of spatial hierarchy and extent through field observations and further studies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_1
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• pp.439-446
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• 2013

This paper is about assessment of soil loss in irrigation reservoir based on GIS. Natural disaster caused by soil loss whose natural incidence has been rapidly reduced due to successful tree planting campaign shows high potential risk, since the latest localized heavy rain resulted from extreme weather event and artificial land development acts as direct factors for land disaster. To prevent it, various techniques and technologies have been used to predict effect of soil loss. However, reliability of techniques and technologies to predict its effect precisely is relatively low so far because the natural disaster by soil loss is taken place by complicated interaction between possible factors and direct factors. Geospatial approach is essential to examine these interactions. In this regard, this study will provide detailed plan to improve prediction reliability for soil loss of irrigation reservoir, using GIS that has Hydrologic -Topographical parameter and digital map as its input parameters.

• Journal of Korea Water Resources Association
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• v.42 no.9
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• pp.737-745
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• 2009

Field measured sediment yield from an experimental urbanized basin was compared with the predicted sediment yields with RUSLE (Revised Universal Soil Loss Equation), and MUSLE (Modified Universal Soil Loss Equation). The experimental basin is 3.1km2 in area and fifty six percent of the total area had been urbanized. The hydrological data have been measured with T/M at the outlet of the experimental basin. Runoff from the basin and rainfall depth of the basin were measured every minute. Bed load and suspended load were also measured for a given flow rate. Runoff rating curves and sediment rating curve were developed for the last three years. RUSLE showed scattered prediction results but the average of the prediction values was close to the measured one. Meanwhile, MUSLE showed linear correlation between the measured sediment yield and predicted one with high correlation coefficient. But MUSLE predicts high values than the real one. Therefore, adjustment is necessary to apply MUSLE in estimation of sediment yield from the experimental urbanized basin.

• Journal of the Korean Geotechnical Society
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• v.28 no.11
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• pp.5-16
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• 2012

Since geologic data are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations, but also to assess the uncertainty attached to the prediction. In this paper, the assessment of the local uncertainty of prediction for the depth to weathered soil was performed by using the indicator kriging. A conditional cumulative distribution function (ccdf) was first modeled, and then E-type estimate was computed for the spatial distribution of the depth to the weathered soil. Also, optimal estimate of spatial distribution for the depth to weathered soil was determined by using ccdf and loss function. The design procedure and method considering the minimum expected loss presented in this paper can be used in the decision-making process for geotechnical engineering design.

• Korean Journal of Soil Science and Fertilizer
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• v.16 no.2
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• pp.112-118
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• 1983

Rainfall factor (R-factor), which is an index for the prediction of soil erosion in the Universal Soil Loss Equation (USLE), was computed from 21 years rainfall data at 51 locations in Korea. The values of R-factor are from 200 to 300 in the eastern part, and 300 to 700 in the western and southern part of the peninsula. Curvilinear regressions exist between annual rainfall and annual R-factor or between monthly rainfall and monthly R-factor. The R-factor can be estimated from the regression equation as a function of the amount of rainfall. According to the comparison between the actual soil loss measured by lysimeter and the soil loss predicted by the USLE, EI 30 for R-factor was recognized as a suitable factor for the USLE in korea.

• Journal of the Korean GEO-environmental Society
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• v.16 no.11
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• pp.29-37
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• 2015

Non-excavation method is needed to secure the stability of existing structures during construction. Therefore, prediction of ground settlement is essential. Causes of settlement when using steel pipe indentation method are leading pipe-steel pipe gap, excessive excavation and soil-steel pipe friction etc. Also they are similar to the causes of settlement when using Shield TBM during construction. In this study, ground settlement during steel pipe indentation is predicted by the Gap Parameter Method and Volume Loss Method which are kinds of Shield TBM prediction Method. and compared with those of prediction methods by conducting field test. As a result, Volume Loss Prediction Method is the most similar to the field tests. However, It is needed to additional studies, such as decision of the factors and adaptability for total settlement predictions of non-excavation method.

• 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.

• Korean Journal of Soil Science and Fertilizer
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• v.9 no.1
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• pp.9-16
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• 1976

In order to investigate inherent erodibility of the soil, which is a major factor is soil erosion prediction, a survey on runoff and soil loss of reclaimed upland soil was carried out by using a portable rainulator. The relations of soil loss and some physical properties of the soil were discussed. The soil erodibility factor for Universal soil loss equation was calculated and compared with that of Wischmeier's nomograph. The result were as follows: 1. Total runoff increased for finer textured soil in order of Jeonnam silty clay loam, Songjeong clay loam, Yesan loam, Samgag and Sangju sandy loam. Total soil loss and soil content in runoff were not correspondently related with textural characteristic in order of Jeonnam, Samgag, Sangju, Yesan, and Songjeong. Total runoff, soil loss, and soil content in runoff were increased for steeper slope. 2. Soil loss and soil content in runoff negatively correlated with organic matter content of surface soil, while positively correlated with dispersion ratio, clay ratio, silt content, and significantly correlated with Middleton erosion ratio for coarser textured soil but not correctly related for finer textured soil. 3. The soil erodibilty factor K values for Universal soil loss equation were 0.32 for Jeonnam, 0.22 for Samgag, 0.17 for Sangju, 0.15 for Yesan, and 0.13 for Songjeong respectively. These values were close to those from Wischmeier's nomograph. So, it seems that the nomograph is useful for estimation of soil loss in Korea.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.843-853
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• 2021

The objectives of this paper were to simply estimate soil loss levels as caused by wind in reclaimed tidal flat land (RTFL) and the threshold wind velocity in the RTFL. For this experiment, RTFL located at Haenam Bay was selected and a total of 150 soil samples were collected at the Ap horizon from the five soil series. The particle distribution curves, including the limit of the non-erodible particle size (D > 0.84 mm) for each Ap horizon soil, show that the proportions of non-erodible particle sizes that exceeded 0.84 mm were 4.3% (Taehan, TH), 8.9% (Geangpo, GP), 0.5% (Bokchun, BC), 1.6% (Poseung, PS) and 1.4% (Junbook, JB), indicating that the amount of non-erodible soil particles increased with an increase in the sand content. The average monthly, daily and instantaneous wind velocities were higher than the threshold friction velocity (TFV) calculated according to the dynamic velocity (V_d) by Bagnold, while the average monthly wind velocity was lower than those of the TFV suggested by the revised wind erosion equation (RWEQ) and wind erosion prediction system (WEPS). The susceptible proportions of erodible soil particles from the Ap horizon soil samples from each soil series could be significantly influenced by the proportion of sand particles between 0.025 and 0.5 mm (or 0.84 mm) in diameter regardless of the threshold wind velocity. Thus, further investigations are needed to estimate more precisely soil erosion in RTFL, which shows various soil characteristics, as these estimations of soil loss in the five soil series were obtained only when considering wind velocities and soil textures.