• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.70-74
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• 2005

Soil particles from rainfall flow into reservoir and give lots of influence In water quality because the geological conditions and landcover characteristics of imha basin have a weakness against soil loss. Especially, much soil particles induced to reservoir in shape of muddy water when it rains a lot because the geological characteristics of imha reservoir are composed of clay and shale layer. Therefore, field turbidity data can be Indirect-standards to estimate the soil erosion of imha basin. This study evaluated annual soil erosion using GIS-based RUSLE (Revised Universal Soil Loss Equation) and developed rainfall weighting value method using time-series rainfall data to estimate monthly soil erosion. In view of field turbidity data(2003 yr), we can find out monthly soil erosion with rainfall weighting value is more efficient than that with monthly rainfall data.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.3
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• pp.108-117
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• 2004

Soil particles from rainfall flow into reservoir and give lots of influence in water quality because the geological conditions and landcover characteristics of Imdong watershed have a weakness against soil loss. Especially, reservoir slant is indicated by the main source area of soil loss. This study selected RUSLE model that could apply GIS and satellite image to evaluate the contribution rate of soil loss in reservoir slant. And we carried out an on-the-spot survey for the range, width and condition of reservoir slant that give much influences to the accuracy of soil loss. As the result of evaluation to the influence of soil loss in reservoir slant, it showed 2.64% in comparison with Imdong watershed. In view of these results, the influence of soil loss in reservoir slant was evaluated in low comparing with Imdong watershed relatively.

• 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 the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.65-73
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• 2005

Because the geological features of Imha basin are composed of clay and shale layer, much soil particle flows into reservoir in shape of muddy water when it rains a lot. Therefore, turbidity data can be indirect-index to estimate the soil erosion of Imha basin. This study evaluated annual soil erosion using GIS-based soil erosion model and applied rainfall weighting value method by time-series rainfall data to estimate monthly soil erosion. In view of 2003 turbidity data, monthly soil erosion with rainfall weighting value is more efficient than monthly soil erosion with rainfall data.

• Journal of Cadastre & Land InformatiX
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• v.45 no.2
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• pp.57-70
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• 2015

Recently, soil erosion have been thickening from heavy rainfall according to climate change. These soil erosion is main reason to cause landslide, the water quality, agricultural counterproductivity and so on. Therefore, it is important to find out the main source area to cause soil erosion using geospatial data including DEM, soil map and land cover those are very sensitive to soil erosion modeling. This study evaluated soil erosion using RUSLE model. Hyoja 4-Dong and Pyonghwa 2-Dong among Wansan-Gu showed high as 10,869 ton/yr and 10,477 ton/yr respectively and Ua 2-Dong of Deokjin-Gu showed high as 17,603 ton/yr in soil erosion. And Hyoja 1-Dong and Pyonghwa 1-Dong among Wansan-Gu showed high as $1,485.7ton/km^2$ and $1,297.0ton/km^2$ respectively and Inhu 3-Dong of Deokjin-Gu showed high as $2,557.7ton/km^2$ in unit soil erosion that was applied to the evaluation of soil erosion potential. It is anticipated that achievement of this study can apply to forecast and prepare the risk of soil erosion and debris flow in urban area.

• Journal of Cadastre & Land InformatiX
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• v.46 no.1
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• pp.59-74
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• 2016

The collapses of retaining walls or embankments, the soil erosion and landslides around urban areas are occurring by heavy rainfalls because of the recent climate change. This study conducts the soil erosion modeling, while applying the spatial information such as soil maps, DEM and landcover maps to the RUSLE model. Especially this study draws up the soil erosion grade map and the unit soil erosion grade map by parcels through coupling the soil erosion with the cadastral map, and by that can calculate the number of parcels by soil erosion grades. Also the sediment disaster information system based on the mobile GIS is developed to identify the soil erosion grades of site in the urban plannings and the construction fields. The sediment disaster information system can identify the present conditions of the registers of lands, buildings and roads, and confirm the RUSLE factors, the soil erosion, the sediment disaster grades by parcels. Also it is anticipated that this system can support the sediment disaster work of site effectively through searching the locations and attributes of the specific parcels by Administrative Dong and the soil erosion grades.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.183-187
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• 2007

유역에서 토사유실로 인한 고농도 탁수의 발생은 현장조사와 수치모형 해석으로 평가될 수 있다. 하지만 현장조사로는 토사유실을 정량화하기에는 제한적이므로 수치모형의 적용이 요구된다. 토사유사예측을 위한 모형 적용 시, 시공간 분석을 위해서 물리적 기반 분포형 혹은 준 분포형 모형이 선호된다. 본 연구에서는 임하 안동 유역의 유출 및 토사유실 분석을 위하여 SWAT 모형 및 HSPF 모형을 적용하였다. 두 모델의 유량 검 보정은 유역 내에 수위 관측 자료(1999년${\sim}$2006년)를 이용하였으며 유사농도는 2006년 하절기 현장 조사를 통해 보정되었다. SWAT 모형의 일별 유출량 변화에 대한 Nash-Sutcliffe 효율계수는 $0.43{\sim}0.76$의 범위로 전반적으로 측정 유량을 잘 모의 하는 것으로 나타났다. HSPF 모형은 SWAT 모형과 마찬가지로 높은 효율의 일별 유출량 예측성을 보였다. 그러나 두 모델은 첨두 유량을 과소산정 하였다. 두 모형의 그래픽 분석결과 측정 유사 농도를 잘 모의하였고, 특히 HSPF 모형은 강우사상에 따른 시간별 실측값의 경향을 잘 예측하였다. 두 모형의 예측성 비교 시, 유출량은 SWAT 모형이 HSPF 모형이 비해 더 잘 모의하였으며 유사 농도는 HSPF 모형이 더 높은 정확성을 보였다. 본 연구의 결과는 향후 각 소유역별로 탁수를 유발하는 토사 유실량 평가, 유역의 토사유실 저감대책 효과분석 및 저수지 모형과의 연계를 통한 유입된 탁수의 효율적인 관리대책 수립에 이용될 것으로 사료된다.

• 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.

• 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.