• Journal of Industrial Technology
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• v.19
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• pp.147-154
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• 1999

The soil loss by rainfalls or runoffs has been one of the main environment problems in 20th century. The soil loss cause the various problems those are decreasing of the agricultural productivity, desolating of pasture land and disturbing of water flowing. Therefore, it is very important to measure properly various factors those are affecting to soil loss and to recognize a seriousness of soil loss problem. In this study, we use the USLE(Universal Soil Loss Equation) as a basic approaching way for soil loss analysis in a watershed, and the GSIS(Geo-Spatial Information System) technique is applied to evaluate for factors those are related to the USLE. The results of this study are consisted of three parts those are to build up the various topographical information that is needed for analysis of wide area soil loss by using the USLE, to evaluate the factors those are needed to the USLE, to estimate the soil loss condition of subbasin in the watershed.

• Journal of Korean Society on Water Environment
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• v.22 no.4
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• pp.619-625
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• 2006

Amount of soil loss is important information for the proper water quality management, In this research, annual average soil loss of the Geum River basin was estimated using RUSLE (Revised Universal Soil Loss Equation) and GIS (Geographic Information System). Input data were manipulated using ArcGIS ver. 8.3. From crop field which constitute 8.2% of the Geum River Basin, annual average soil loss was estimated as 53.6 ton/ha/year. From the rice paddy field which constitutes 20% of the Geum River Basin, soil loss was estimated as 33.5 ton/ha/year, In comparison, forestry area which constitutes 61.8% of the basin discharged 2.8 ton/ha/year, It could be known from this research that appropriate measures should be implemented to prevent excessive soil loss from the agricultural areas.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.3
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• pp.29-42
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• 2023

Universal Soil Loss Equation (USLE) is suggested and employed in the policy to conserve soil resources and to manage the impact of development, since soil loss is very essential to nonpoint source pollution management. The equation requires only five factors to estimate average annual potential soil loss, USLE is simplicity provides benefits in use of the equation. However, it is also limitation of the model, since the estimated results are very sensitive to the five factors. There is a need to examine the application procedures. Three approaches to estimate potential soil loss were examined, In the first approach, all factors were prepared with raster data, soil loss were computed for each cell, and sum of all cell values was determined as soil loss for the watersheds. In the second approach, the mean values for each factor were defined as representing USLE factors, and then the five factors were multiplied to determine soil loss for the watersheds. The third approach was same as the second approach, except that the Vegetative and Mechanical measure was used instead of the Cover and management factor and Support practice factor. The approaches were applied in 38 watersheds, they displayed significant difference, moreover no trends were detected for the soil loss at watersheds with the approaches. Therefore, it was concluded that there is a need to be developed and provided a typical guideline or public systems so that soil loss estimations have consistency with the users.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.3
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• pp.77-85
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• 2007

Assessment of soil erosion is a cost and time-consuming task. There are many models developed to predict soil erosion from an area, but Universal Soil Loss Equation (USLE) is most widely used empirical equation for estimating annual soil erosion. Soil erosion depends upon-rainfall intensity, type of soil, land cover and land use, slope degree, slope length and soil conservation practice. All these parameters are have spatial distribution and hence satellite remote sensing and Geographic Information System (GIS) are applicable in the assessment of the influence on soil erosion. GIS has been integrated with the USLE (Universal Soil Loss Equation) model in identification of rainfall-based erosion to the Bocheong River which is the representative basin of IHP due to Typhoon Rusa. Similar studies are available in literature, ranging from those that use a simple model such as USLE to others of a more sophisticated nature.

• 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 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 GEO-environmental Society
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• v.20 no.3
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• pp.5-14
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• 2019

This study attempted to study the soil erosion dynamic in the Bagmati Basin of Nepal. In this study, an inclusive methodology that combines Revised Universal Soil Loss Equation (RUSLE) and GIS techniques was adopted to determine the distribution of soil loss in the study basin. As well, this study attempts to study the intensity of soil erosion in the seven different land use patterns in the Bagmati Basin. Soil loss is an associated phenomenon of hydrologic cycle and this dynamic phenomenon possesses threats to sustainability of basin hydrology, agriculture system, hydraulic structures in operation and overall ecosystem in a long run. Soil conservation works, and various planning and design of watersheds works demands quantification of soil loss. The results of the study in Bagmati Basin shows the total annual soil loss in the basin is 22.93 million tons with an average rate of 75.83T/ha/yr. The computed soil loss risk was divided into five classes from tolerable to severe and the spatial pattern was mapped for easy interpretation. Also, evaluation of soil loss in different land use categories shows barren area has highest rate of soil loss followed by agriculture area. This is a preliminary work and provides erosion risk scenario in the basin. The study can be further used for strategic planning of land use and hydrologic conservation works in a basin.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.1
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• pp.112-117
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• 2012

The Revised Universal Soil Loss Equation (RUSLE) is a revision of the Universal Soil Loss Equation (USLE). However, changes for each factor of the USLE have been made in RUSLE which can be used to compute soil loss on areas only where significant overland flow occurs. RUSLE which requires standardized methods to satisfy new data requirements estimates soil movement at a particular site by utilizing the same factorial approach employed by the USLE. The rainfall erosivity in the RUSLE expressed through the R-factor to quantify the effect of raindrop impact and to reflect the amount and rate of runoff likely is associated with the rain. Calculating the R-factor value in the RUSLE equation to predict the related soil loss may be possible to analyse the variability of rainfall erosivity with long time-series of concerned rainfall data. However, daily time step models cannot return proper estimates when run on other specific rainfall patters such as storm and daily cumulative precipitation. Therefore, it is desirable that cross-checking is carried out amongst different time-aggregations typical rainfall event may cause error in estimating the potential soil loss in definite conditions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.141-147
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• 2006

Soil losses are occurred by rainfall has caused productivity decline of a fertile surface soil and inflow sediment on Dam reservoir which are the main reasons of the decrease of storage volume and difficulty of water management. In this study, the amount and location of soil losses which were evaluated using USLE(Universal Soil Loss Equation) were applied on soil, landcover, and topographical conditions on the basis of satellite images and GIS. Furthermore, it was possible to evaluate the amount of riverbed sediments using echo-sounder and sediment rate were analyzed by comparing with soil losses.

• 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.