• Journal of Industrial Technology
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• v.30 no.B
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• pp.99-108
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• 2010

This study was intended to estimate the soil runoff at the basin of Mandaechun where the measure needs to be taken to deal with the increasing muddy water resulting from soil runoff during wet season and torrential rain at the high reaches of the Soyang lake where highland vegetables are cultivated and soil replacement for improvement is carried out every two to three years. The study was carried out in such a way of identifying the topographic factors using geographical spatial data from Water Management Information System (WAMIS) and ARC-VIEW program and estimating the soil runoff by rainfall frequency using Revised Universal Soil Loss Equation (RUSLE), and furthermore, evaluating the soil runoff contribution at the basin of Mandaechun based on estimate of the soil runoff by section.

• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.603-610
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• 2000

Climate factors such as rainfall, temperature, wind, humidity, and solar radiant heat affect soil erosion. Among those factors, rainfall influences soil erosion to the most extent. The kinetic energy of rainfall breaks away soil particles and the water flow caused by the rainfall entrains and transport them downstream. In order to estimate soil erosion, therefore, it is important to determine the rainfall erosivity. In this study, the annual average Rainfall Erosivity(R) in Korea, an important factor of the Universal Soil Loss Equation(USLE) and Revised Equation(RUSLE), has been estimated using the nationwide rainfall data from 1973 to 1996. For this estimation, hourly rainfall data at 53 meterological stations managed by the Meterological Agency was used. It has been found from this study that the newly computed values for R are slightly larger than the existing ones. It would be because this study is based on the range of rainfall data that is longer in period and denser in the number of gauging stations than what the existing result used. The final result of this study is shown in the form the isoerodent map of Korea.

• Spatial Information Research
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• v.14 no.4 s.39
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• pp.363-377
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• 2006

Mean annual soil loss was calculated and critical soil erosion areas were identified for the Congaree River Basin in South Carolina, USA using the Revised Universal Soil Loss Equation (RUSLE) model. In the RUSLE model, the mean annual soil loss (A) can be calculated by multiplying rainfall-runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), crop-management (C), and support practice (P) factors. The critical soil erosion areas can be identified as the areas with soil loss amounts (A) greater than the soil loss tolerance (T) factor More than 10% of the total area was identified as a critical soil erosion area. Among seven subwatersheds within the Congaree River Basin, the urban areas of the Congaree Creek and the Gills Creek subwatersheds as well as the agricultural area of the Cedar Creek subwatershed appeared to be exposed to the risk of severe soil loss. As a prototype model for examining future effect of human and/or nature-induced changes on soil erosion, the RUSLE model customized for the area was embedded into ESRI ArcGIS ArcMap 9.0 using Visual Basic for Applications. Using the embedded model, users can modify C, LS, and P-factor values for each subwatershed by changing conditions such as land cover, canopy type, ground cover type, slope, type of agriculture, and agricultural practice types. The result mean annual soil loss and critical soil erosion areas can be compared to the ones with existing conditions and used for further soil loss management for the area.

• 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.

• 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.

• Spatial Information Research
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• v.13 no.1 s.32
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• pp.79-90
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• 2005

The purpose of this study is to estimate quantitatively soil loss and sediment yield in alpine farmland. For this purpose, Naerinchon watershed in Gangwon province was selected as our study area and total annual soil loss and sediment yield was estimated respectively by the Revised Universal Soil Loss Equation (RUSLE) model and the Sediment Delivery Distributed (SEDD) model. The results of this study clearly show that dry field areas have significant impact on the total soil erosion and sediment yield compared with other land use. Dry field areas represent only $2.6\%$ of the total area of the watershed but soil loss and sediment yield account for $10.9\%$ and $33.12\%$ of the total amount respectively Especially as with alpine farmland, this result is more clearly shown. These areas account for $1.8\%$ of the entire watershed but contribute to $7.7\%$ and $15\%$ of the total soil loss and sediment yield respectively. From the above results, we can know that alpine farmland is important source of soil loss and sediment yield and it is need to prevent and control. soil erosion from alpine filmland urgently.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.341-347
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• 2006

Geographically Imha basin is adjacent to Andong basin, but the occurrence of turbid water in each reservoir by storm events shows big differences. Hence, it is very important to identify the reason for these large differences. This study compared and analyzed soil erosion using the semi-empirical soil erosion model, RUSLE for both Imha and Andong basin, especially with emphasis on high-density turbid water. The agricultural district, which is the most vulnerable to soil erosion, was intensively analyzed based on land cover map produced by Ministry of Environment. As a result, the portion of the agricultural area is 11.88% for Andong basin, while it is 14.95% for Imha basin. Also all RUSLE factors excepts practice factor turned out to be higher for Imha basin. This means that the basin characteristics such as soil texture, terrain, and land cover for Imha basin is more vulnerable to soil erosion. Estimation of soil erosion by RUSLE for Andong and Imha basin is 1,275,806 ton and 1,501,608 ton, respectively, showing higher soil erosion by 225,802 ton for Imha basin.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.430-430
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• 2016

범용토양유실공식(RUSLE)은 연간 토양유실량을 산정하기 위해 제시된 경험식이며, 강우침식인자(R factor)는 유실량을 결정하는 요소 중 강우강도의 특성을 고려하는 주요인자이다. 토지피복, 식생 등에 대한 타 인자의 경우 한정된 실험에 의해 도출된 경험치를 대상지역에 맞게 적용하는데 반해 강우침식인자는 강우강도 기반 강우에너지 산정법을 적용하여 계산과정이 비교적 복잡하고 다양하다. 국내에서도 강우침식인자 산정법이 개발된 바 있으나 현제까지 간편법을 비롯한 다양한 공식들이 적용되고 있다. 본 연구에서는 강우침식인자를 산정하는 과정에서 다른 강우 운동에너지식을 적용하거나 연평균 강수량 등을 대체지수로 활용한 간편법 적용시 결과의 결과의 다양성에 대해 분석하고자 하였다. 합리적인 30분 강우강도 산정을 위해 79개 기상청 종관기상관측 지점에 대한 분단위 강우자료(1997~2014)를 수집하고 기존의 국내외 강우운동에너지 식과 대체지수를 적용하여 산정된 결과를 비교 분석하였다. 연구결과 간편법을 사용한 결과가 대부분 지점에 대해 강우에너지식을 사용한 강우침식인자보다 과대산정(지점평균 약 74%)하였으며 다른 강우에너지식 적용에 따른 평균 변동계수가 약 0.12로 나타나 지점간 차이를 보였으나 적용방법에 따른 침식인자의 분포가 다소 다르게 나타남을 확인하였다. 관측자료가 부족한 토양유실량 예측에 있어 강우 침식인자 산정을 위한 최적 방법론 도출이 어려운 만큼 다중모델 결과를 조합하는 방법론 개발이 필요하다고 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.114-114
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• 2016

토양유실에 영향을 미치는 기후 인자로는 강우, 기온, 바람, 습도 및 태양열 복사 등이 있다. 이들 중 강우는 토양침식에 직접적인 영향을 미치는 인자로 토립장의 이탈로 인한 토양침식을 유발한다. 토양침식을 예측하는데 있어 강우의 영향을 나타내는 지표의 설정은 매우 중요하다. 이러한 강우침식인자는 각 강우사상에 대한 강우에너지와 30분 최대 강우강도의 곱의 합으로 정의된다. 강우침식도를 정확하게 계산하기 위해서는 다년간 측정된 분단위 강우자료가 필요하며, 강우자료 획득의 제한과 강우의 분류 및 계산과정 등이 복잡하여 실무적으로 산정하기 어려운 점이 있다. 본 연구에서는 1분 상세강우자료를 이용하여 개정범용토양유실공식(RUSLE)의 강우침식도 R의 추정을 위해 2001년부터 2015년까지 15년간 전국 61개 기상청 관측소의 강우 자료를 수집하여 지점별로 새롭게 계산한 연 강우침식도 및 경험식을 산정하였으며 남한전체($99,720km^2$)를 대상으로 연 강우침식량의 공간분포맵을 작성하였다. 지점별 산정된 경험식은 연평균 강우량과 1분 강우자료로부터 산정된 강우침식도와의 상관관계로 회귀식을 도출하였다. 1분 강우자료로 계산된 강우침식도와 연평균 강우량의 상관관계로부터 도출된 경험식과의 결정계수($R^2$, determination coefficient)는 0.70 ~ 0.98로 높은 상관관계를 나타냈으며 또한, 기존의 국내에서 적용된 경험식과 비교하여 평균 $R^2$가 0.59에서 0.80로 실측값과의 정확성이 높게 개선됨을 알 수 있다.