• 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.

• Journal of Soil and Groundwater Environment
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• v.17 no.6
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• pp.119-128
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• 2012

The applicability and accuracy of Revised Universal Soil Loss Equation (RUSLE) model on the estimation of soil loss at impacted area of shooting range was tested to further the understanding of soil erosion at shooting ranges by using RUSLE. At a shooting range located in northern Kyunggi, the amount of soil loss was estimated by RUSLE model and compared with that estimated by Global Positioning System-Total Station survey. As results, the annual soil loss at a study site (202 m long by 79 m wide) was estimated to be 2,915 ton/ha/year by RUSLE and 3,058 ton/ha/year by GPS-TS survey, respectively. The error between two different estimations was less than 5%, however, information on site conditions should be collected more to adjust model coefficients accurately. At the study shooting range, sediments generated by rainfall was transported from the top to near the bottom of the sloping face through sheet erosion as well as rill erosion, forming a gully along the direction of the storm water flow. Coarser fractions of the sediments were redeposited in the limited area along the channel. Distribution characteristics of explosive compounds in soil before and after summer monsoon rainfall in the study area were compared with the erosion patterns. Soil sampling and analyses results showed that the dispersion of explosive compounds in surface soil was consistent with the characteristics of soil erosion and redeposition pattern of sediment movements after rainfalls.

• Journal of the Korean GEO-environmental Society
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• v.3 no.4
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• pp.19-27
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• 2002

Prediction of exact soil loss yield has as important engineering meaning as prediction of exact flow measurement in a stream. The quantity of soil loss in a stream should be considered in planning and management of water resources and water quality such as design and maintenace of hydraulic structures : dams, weirs and seawalls, channel improvement, channel stabilization, flood control, design and operation of reservoirs and design of harbors. In this study, the soil loss of Sap-gyo reservoir watershed is simulated and estimated by RUSLE model which is generally used in the estimation of soil loss. The parameters of RUSLE model are selected and estimated using slope map, landuse map and soil map by GIS. These parameters are applied to RUSLE's estimating program. And soil loss under probability rainfall in different frequencies are estimated by recent 30 years of rainfall data of Sap-gyo reservoir watershed.

• Journal of Korean Society of Forest Science
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• v.103 no.1
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• pp.98-104
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• 2014

This study aims to predict the amount of soil loss from Mt. Palgong's small basin, by using influence factors derived from related models, including RUSLE and MUSLE models, and verify the validity of the model through a comparative analysis of the predicted values and measured values, and the results are as follows: The amount of soil loss were greatly affected by LS factor. In comparison with the measured value of the amount of total soil loss, the predicted values by the two models (RUSLE and MUSLE), appeared to be higher than those of the measured soil loss. Predicted values by RUSLE were closer to values of measured soil loss than those of MUSLE. However, coefficient of variation of MUSLE were lower, but two model's coefficient of variation in similar partial patterns in the prediction of soil loss. RUSLE and MUSLE, prediction soil loss models, proved to be appropriate for use in small mountainous basin. To improve accuracy of prediction of soil loss models, more effort should be directed to collect more data on rainfall-runoff interaction and continuous studies to find more detailed influence factors to be used in soil loss model such as RUSLE and MUSLE.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.495-499
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• 2012

토사유출량이란 강우가 발생한 지점에서 토양침식에 의해 생산된 토사가 퇴적 및 이송 등의 과정을 거쳐 유역의 특정 지점까지 도달한 토사량을 의미한다. 토사유출량을 정확하게 산정하는 방법은 현재까지 없다. 그러나 유역단위의 대략적인 토사유출량 산정을 위해서는 경험적 모형인 USLE 모형과 수정된 형태의 RUSLE 모형 또는 MUSLE 모형이 보편적으로 사용되고 있다. 최근에는 지형정보시스템(GIS)의 발달로 RUSLE 모형과 MUSLE 모형이 주로 사용되는데 연평균 토사량 산정에는 RUSLE 모형이 사용되며 단일호우에 대한 토사량은 MUSLE 모형이 사용된다. 그러나 이 모형들은 구곡 및 하천에서의 수리학적 특성 반영하기 힘든 단점이 있어서 유출지점에 따라 유사전달률(SDR)의 개념이 요구된다. RUSLE 모형과 MUSLE 모형에 사용되는 유사전달률은 외국에서의 경험적 공식으로서 우리나라 유역 실정을 제대로 반영하지 못하는 단점이 있다. 그러므로 추후 연구에는 8~10년 이상의 토사유출량 자료를 바탕으로 그 유역의 유사전달률을 결정하고, 그 결과 값을 이용하여 단일호우 사상의 유출량과 모의유출량을 비교하여 MUSLE 모형의 강우인자인 R값을 산정해야 할 것으로 판단된다. 그 선행 작업으로, 본 연구에서는 RUSLE 모형과 기존의 유사전달률을 사용하여 낙동강 상주보까지의 토사유출량을 산정하였다. 상주보유역은 안동댐유역, 임하댐유역, 안동댐하류유역, 내성천유역, 영강유역으로 구성되며 안동댐유역과 임하댐유역은 댐의 차단으로 본 연구의 토사유출량 산정에서 제외하였다.

• 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 Korean Society for Geospatial Information Science
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• v.12 no.4 s.31
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• pp.75-81
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• 2004

Because geological types and land cover conditions of Imha basin have a very weak characteristics to soil erosion, most soil particles (low into river and bring about high density turbidity in Imha reservoir when it rains a lot. This study used GIS-based RUSLE model and analyzed soil erosion to make basic data for the countermeasures of turbidity reduction in Imha reservoir. Total soil erosion amounts was evaluated as 5,782,829 ton/yr using rainfall data(2003) and especially Dongbu-basin was extracted as most source area or soil erosion among Imha sub-basin. Also it was evaluated that soil erosion amount by RUSLE model was suitable by applying turbidity survey data.

• Spatial Information Research
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• v.10 no.2
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• pp.301-316
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• 2002

Soil Loss by outflow of water or rainfall has caused many environmental problems as declining agricultural productivity, damaging pasture and preventing flow of water. Also, validity pondage of reservoir or dam is decreased by rivers inflow of eroded soil. Revised Universal Soil Loss Equation(RUSLE) is mainly used to presume soil loss amount of basin using GIS. But, because comparison with survey data is difficult, it is no large meaning that estimate calculated soil loss amount as quantitative. This research used unit sediment deposit survey data of Bo-seong basin for quantitative conclusion of soil loss amount that calculate on RUSLE. Through comparison examination with unit sediment yield that calculate on RUSLE and unit sediment deposit survey data, we can estimate resolution far RUSLE Model. As a result, cell size of 150m was estimated by thing which is most suitable.

• 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 Association of Geographic Information Studies
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• v.6 no.3
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• pp.1-10
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• 2003

RUSLE(revised universal soil loss equation) has been widely used for estimating soil loss. It is very difficult to validate the model estimation since the calculated soil loss should be compared with the survey data for quantification. The input variables for RUSLE model were estimated to grid cell for raster analysis in Bosung basin. Both reconnaissance(1:250,000) and detailed(1:25,000) soil maps were used to derive the input variables for soil erodibility factor. Soil loss calculated using RUSLE were compared to the unit sediment deposit surveyed by KICT(Korea Institute of Construction Technology, 1992) in Bosung basin for assessment. Unit sediment deposit from the cell size of 120m and 150m were the closest to the survey data in 1:250,000 and 1:25,000 map scale, respectively.