• 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 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.

• 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.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.515-524
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• 2016

Damage such as landslides has been caused by natural phenomenon like a heavy rain. As appropriate countermeasures, rather than analysing the cause of the landslide, we used methods of check dam installation and maintenance mountain basin. A check dam is a small, sometimes temporary, dam constructed across a swale, drainage ditch, or waterway to counteract erosion by reducing water flow velocity. In this study, we analysed the adequacy of check dam built to prevent further damage after landslides through GIS and examined the sediment erosion in the existing check dams for an ideal location of check dam, considering the accessibility and size. As a result of reviewing soil loss in the study watershed according to RUSLE(Revised Universal Soil Loss Equation), the basin I had about 2% soil loss reduction, the basin II showed less than 1 % soul loss reduction, and basin III showed the reducing effect of 5 % soil erosion.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.274-277
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• 2007

This study is to estimate the spatial distribution of soil loss using the land use data produced from QuickBird satellite imagery. For a small agricultural watershed (1.16 $km^2$) located in the upstream of Gyeongan-cheon watershed, a precise agricultural land use map were prepared using QuickBird satellite image of April 5 of 2003. RUSLE (Revised Universal Soil Loss Equation) was adopted for soil loss estimation. The data (DEM, soil and land use) for the RUSLE were prepared for 5 m and 30 m spatial resolution. The results were compared with each other and the result of 30 m Landsat land use data.

• 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.

• 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 Soil and Groundwater Environment
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• v.19 no.6
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• pp.30-36
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• 2014

The objective of this study is to estimate soil loss in the buffer zone of Guem river with future climate change simulation. Revised Universal Soil Loss Equation (RUSLE) model was used for the estimation of soil loss at the buffer zone of Guem river. As results of simulations, the area of the maximum soil loss potential was estimated as the Cheongsung-myeon Okchun-gun Chungcheongbuk-do. The soil losses were estimated to be 106.67 and 103.00 ton/ha/yr for the 2020 segi (2015-2025) and 2040 segi (2035-2045) in the Cheongsung-myeon area, respectively. Also, the estimated average values of soil losses in the Cheongsung-myeon with future climate change was 110.78 ton/ha/yr.

• 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.