• Journal of Environmental Impact Assessment
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• v.15 no.1
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• pp.1-12
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• 2006

Changes in the soil physical property and the topographic condition derived from agricultural activities like as farming activities, land clearance and cutting down resulted in environmental and economic problems including the outflow of nutrient from farms and the water pollution. Several theories on the soil conservation have been developed and reviewed to protect soil erosion in the regions having a high risk of erosion. This study was done using the USLE model developed by Wischmeier and Smith (1978), and model for the slope length and steepness made by Desmet and Govers (1996), and Nearing (1997) to evaluate the potential of the soil erodibility. Therefore, several results were obtained as follows. First, factors affecting the soil erosion based on the USLE could be extracted to examine the erosion potential in farms. Soil erodibility (K), slope length (L), and slope steepness (S) were used as main factors in the USLE in consideration of the soil, not by the land use or land cover. Second, the soil erodibility increased in paddy soils where it is low in soil content, and the very fine sandy loam exists. Analysis of the slope length showed that the value of a flat ground was 1, and the maximum value was 9.17 appearing on the steep mountain. Soil erodibility showed positive relationship to a slope. Third, the potential soil erodibility index (PSEI) showed that it is high in the PSEI of the areas of steep upland and orchard on the slope of mountainous region around Dokjigol mountain, Dunji mountain, and Deummit mountain. And the PSEI in the same land cover was different depending on the slope rather than on the physical properties in soil. Forth, the analysis of land suitability in soil erosion explained that study area had 3,672.35ha showing the suitable land, 390.88ha for the proper land, and 216.54ha for the unsuitable land. For unsuitable land, 8.71ha and 6.29ha were shown in fallow uplands and single cropping uplands, respectively.

• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.357-372
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• 2006

The excessive land activities in farming can cause soil erosion, inundation by a flood, and fallow. So far land evaluation has been analyzed using the land use limitation derived from the excessive land activities. This study was done for evaluating the agricultural fields by using 3 land use limitations, inundation potential, soil erodibility potential, and fallow potential. The study area is Ibang-myeon, Changnyeong-gun, Gyeongnam-province, Korea. A logistic regression model was applied to recognize the inundation potential by a flood in the Nakdong river basin. And potential soil erodibility index (PSEI) was derived from USLE model to analyze the soil erodibility potential. And a probability model from a logistic regression model was applied to detect the fallow potential. Therefore, we found 220.7ha for the 4th grade and 86.1ha for the 5th grade was analyzed as water damage potential. Large area near Nakdong river have problem to grow the rice due to the damage by water inundation. And 213.6ha for the 3rd grade and 103.3ha for 4th grade was detected as a result of the analysis of soil erosion potential. The soil erosion potential was high when within-field integrity of soil was not stable, or the kinetic energy was high or the slope length was long due to a steep slope of a specific land. And 869.1ha for 3rd grade, 174.9ha for 4th grade, and 110.6ha for 5th grade was detected to be distributed having the fallow potential. Especially, a village, having a steep mountain, had 249.5ha for the 3rd grade, which was 28.7% of total area showing the 3rd grade. Finally, Three villages, including An-ri, Geonam-ri, Songgok-ri, showed they had largest area of the suitable land in the study area. These villages had similar topographic condition where they were far from Nakdong river, and they had relatively higher elevation and flat lands.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.6
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• pp.119-124
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• 2009

In this study, the characteristics of estimating methodology for RUSLE factors such as soil erodibility factor, slope length-steepness factor, and cover management factor were reviewed and then the relative error according to each methodology was analyzed. RUSLE was applied to experimental watershed for 42 storm events and their results were compared with measured sediment yield to examine the applicability of RUSLE. As a result, this paper found that it should be necessary to consider vegetation effect for forest application of RUSLE as cover management was the most sensitive factor. Also, soil erodbility factor was calculated from data of soil series by National Academy of Agricultural Science caused sediment yield to be overestimated because there were big differences between the soil series and on-site soil texture. The 22.7% of maximum relative error was shown according to selecting the rain energy equation. In addition, it will be necessary to verify the RUSLE factors with more data in order to improve their accuracy.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.6
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• pp.23-30
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• 2016

Soil loss is an accompanying phenomenon of hydrologic cycle in watersheds. Both rainfall drops and runoff lead to soil particle detachment, the detached soil particles are transported into streams by runoff. Here, a sediment-laden water problem can be issued if soil particles are severely detached and transported into stream in the watershed. There is a need to estimate or simulate soil erosion in watersheds so that an adequate plan to manage soil erosion can be established. Universal Soil Loss Equation (USLE), therefore, was developed and modified by many researchers for their watersheds, moreover the simple model, USLE, has been employed in many hydrologic models for soil erosion simulations. While the USLE has been applied even in South-Korea, the model is often regarded as being limited in applications for the watersheds in South-Korea since monthly conditions against soil erosion on soil surface are not capable to represent. Thus, the monthly USLE factors against soil erosion, soil erodibility and crop management factors, were established for four major watersheds, which are Daecheong-dam, Soyang-dam, Juam-dam, and Imha-dam watersheds. The monthly factors were established by recent fifteen years from 2000 to 2015. Five crops were selected for the monthly crop management factor establishments. Soil loss estimations with the modified factors were compared to conventional approach that is average annual estimations. The differences ranged from 9.3 % (Juam-dam watershed) to 28.1 % (Daecheong-dam watershed), since the conventional approaches were not capable of seasonally and regionally different conditions.

• Journal of the Korean Institute of Landscape Architecture
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• v.24 no.3
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• pp.115-132
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• 1996

The purpose of this study is to estimate the soil loss amount with Geographic Information System according to the land use change of Buju mountain area in Mokpo city. To estimate the soil loss, Universal Soil Loss Equation which is the most proper technique to predict soil loss in this site condition is adopted and IDRISI, a raster GIS software, is used. GIS application with USLE is very efficient to estimate soil loss accurately and fastly. In order to decide value and to find application method of USLE factors, we used existing rainfall erosion index, soil erodibility analysis, slope length, slope steepness, vegetation management and practices, which are rated by GIS through the analysis of various studies related USLE. The result of this study was compared with the previous other researches to verify our method of constructing numerical data of USLE's factors. The result of verification of our way showed significance for the soil loss in forest area. But the result of verification for the soil loss in forest area. But the result of verification for the soil loss of cultivated area showed some errors. It seems that this result was due to local variation of topographical map.

• 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 the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.89-97
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• 2006

Soil erosion has caused serious environmental problems which threaten the foundation of natural resources. In this paper, we chose RUSLE erosion model, which could be connected easily with GSIS and available generally in mid-scale watershed among soil erosion models, and extracted factors entered model by using GSIS spatial analysis method. First, this study used GIS database as soil map, DEM, land cover map and rainfall data of typhoon Memi (2003) to analyze soil loss amount of Dam basin. To analyze the changes of soil loss in considering basin characteristics as up-, mid- and downstream, this study calculated soil erodibility factor (K), topographic factors (LS), and cover management factor (C). As a result of analysis, K and LS factors of upstream showed much higher than those of downstream because of the high ratio of forest. But C factor of downstream showed much higher than that of upstream because of the high ratio of agricultural area. As a result of analysis of soil loss, unit soil loss of upstream is 4.3 times than soil loss of downstream. Therefore, the establishment of countermeasures for upstream is more efficient to reduce soil loss.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.1
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• pp.27-37
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• 2001

Soil erosion by outflow of water or rainfall has caused many environmental problems as declining agricultural productivity, damaging pasture and preventing flow of water. As the interest in environment is increasing lately, soil erosion is considered as a serious problem, whereas the systematic regulation and analysis for that have not established yet. This research shows the method of extracting factor entered model which expects soil erosion by GSIS. There are several erosion model such as ANSWER, WEPP, RUSLE. The research used RUSLE erosion model which could expect general soil erosion connected easily with GSIS data. RUSLE's input factors are composed of rainfall runoff factor(R). soil erodibility factor(K), slope length factor(L), slope steepness factor(S), cover management factor(C) and support practice factor(P). The general equation used to extract L, S factor on the RUSLE to be oriented for agricultural area has some limitation to apply whole watershed. So, on this study we used a revised empirical equation applicable to the watershed by grid on the GSIS. Also, we analyzed RUSLE factors by watershed being analyzed with watershed extraction algorithm. Then we could calculate the minimum, maximum. mean and standard deviation of RUSLE factors by watershed.

• Spatial Information Research
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• v.2 no.2
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• pp.165-174
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• 1994

Soil loss was estimated by using universal soil loss equation(USLE) through GIS technique in Buyeu area. The expected soil loss is determined from six environmental factors: rainfall, erodibility of selected soil, length and steepness (gradient) of ground slope, crop grown in soil, and land practices used. A scoring system for assessing soil lossrisk has been developed for calculating SLI(Soil Loss Index) by GIS. The scores of six factors multiplied to give a total score which was compared with an chosen classification system to categorize areas of low, moderate and high risk. Finally, a soil loss assessment map was produced by GIS cartographic simulation technique, and this map could be applied in the establishment of regional land use planning.

• 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.