• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.771-776
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• 1999

RUSLE was applied to estimate annual soil loss from two small agricultural watersheds in Kangwon-do, Korea. GIS input parameters were prepared by using DEMs and soil maps prepared by the NGIS project and Rural Development Adminstration, respoctively. RUSLE parameters were prepared based on existing data and equations. Estimated annual soil loss was graphically presented to easily visualize the large soil loss area. Uplands and vineyards proved to be the two greatest sources for soil erosion. It was suggested to develop effective management practices to reduce the soil erosion from uplands and vineyards.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.126-131
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• 2007

The Imha watershed is vulnerable to severe erosion due to the topographical characteristics such as mountainous steep slopes. The RUSLE model was combined with GIS techniques to analyze the mean annual erosion losses and the soil losses caused by typhoon "Maemi". The model is used to evaluate the spatial distribution of soil loss rates under different land uses. The mean annual soil loss rate and soil losses caused by typhoon "Maemi"were predicted as $3,450\;tons/km^2/year$ and $2,920\;ton/km^2/"Maemi"$, respectively. The sediment delivery ratio was determined to be about 25% from the mean annual soil loss rate and the surveyed sediment deposits in the Imha reservoir in 1997.

• Water Engineering Research
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• v.7 no.1
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• pp.29-41
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• 2006

The Imha watershed is vulnerable to severe erosion due to the topographical characteristics such as mountainous steep slopes. Sediment inflow from upland area has also deteriorated the water quality and caused negative effects on the aquatic ecosystem of the Imha reservoir. The Imha reservoir was affected by sediment-laden density currents during the typhoon 'Maemi' in 2003. The RUSLE model was combined with GIS techniques to analyze the mean annual erosion losses and the soil losses caused by typhoon 'Maemi'. The model is used to evaluate the spatial distribution of soil loss rates under different land uses. The mean annual soil loss rate and soil losses caused by typhoon 'Maemi' were predicted as 3,450 tons/km2/year and 2,920 ton/km2/'Maemi', respectively. The sediment delivery ratio was determined to be about 25% from the mean annual soil loss rate and the surveyed sediment deposits in the Imha reservoir in 1997. The trap efficiency of the Imha reservoir was calculated using the methods of Julien, Brown, Brune, and Churchill and ranges from 96% to 99%.

• 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 of Rural Planning
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• v.11 no.2 s.27
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• pp.9-19
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• 2005

The purpose of this study is to analyze the potential soil loss and hazard zone by the Revised Universal Soil Loss Equation(RUSLE) for preservation and management of land resources which is the base of ecosystem, and to grasp the relationship between RUSLE factors in the Nakdong River Basin. All thematic maps used in RUSLE are constructed through GIS and spatial analysis method derived from digital topographic maps, detailed soil maps, land-cover maps, and mean annual precipitation of 30 years collected respectively from National Geographic Information Institute, National Institute of Agricultural Science and Technology, and Ministry of Environment. The slope length of LS-factor that takes much times by the study area's wideness was calculated automatically through AML(Arc Macro Language) program developed by Van Remortel et al.(2001, 2003). The results are as follows; First, according to the soil loss estimation by the RUSLE, it shows that approximately 82% of the study area have relatively lower possibility of soil loss which is the 1 ton/ha in annual soil loss. While, 9.4% ($2,228km^2$) needed intensive and continuous management for soil loss. Because the amount of their annual soil loss was greater than 10 ton/ha that is optimum level suggested by Morgan(1995). For these areas, the author believe that a new approach which can minimize environmental impacts from soil loss through improvement of cultivation process and buffer forest zone should be applied. Second, according to the relationship between the RUSLE factors, topographical(LS-factor) and cover management(C-factor) conditions have a lot of influence on soil loss in case of the Nakdong River Basin. However, because of RUSLE factor's influence that affect to soil loss might be different based on the variety of spatial hierarchy and extent, it is necessary to analyze and evaluate factor's relationship in terms of spatial hierarchy and extent through field observations and further studies.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.517-524
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• 2014

The ultimate goal of seismic design is to reduce the probable losses or damages occurred during an expected earthquake event. To achieve this goal, this study represents a procedure that can estimate annual loss probability of a structure damaged by strong ground motion. First of all, probabilistic seismic performance assessment should be performed using seismic fragility analyses that are presented by a cumulative distribution function of the probability in each exceedance structural damage state. A seismic hazard curve is then derived from an annual frequency of exccedance per each ground motion intensity. An annual loss probability function is combined with seismic fragility analysis results and seismic hazard curves. In this paper, annual loss probabilities are estimated by the structural fragility curve of steel moment-resisting frames(SMRFs) in San Francisco Bay, USA, and are compared with loss estimation results obtained from the HAZUS methodology. It is investigated from the comparison that seismic losses of the SMRFs calculated from the HAZUS method are conservatively estimated. The procedure presented in this study could be effectively used for future studies related with structural seismic performance assessment and annual loss probability estimation.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1004-1009
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• 2011

Soil erosion in North Korea has been continued to accelerate by deterioration of topographical conditions. However, few studies have been conducted to predict the amount of soil loss in North Korea due to limited data so far. Rainfall erosivity is an important factor to predict the amount of long-term annual soil loss by USLE (universal soil loss equation). The purpose of this study is to investigate rainfall erosivity, which presented the potential risk of soil erosion by water, in North Korea. Annual rainfall erosivities for 27 stations in North Korea for 1983~2010 were calculated using regression models based on modified Institute of Agricultural Sciences (IAS) index in this study. The result showed that annual average rainfall erosivity in North Korea ranged from 2,249 to 7,526 and averaged value was $4,947MJmm\;ha^{-1}\;hr^{-1}\;yr^{-1}$, which corresponded to about 70% of annual average rainfall erosivity in South Korea. The finding was that the potential risk of soil erosion in North Korea has been accelerated by the increase of rainfall erosivity since the late 1990s.

• The Korean Journal of Ecology
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• v.9 no.1
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• pp.59-71
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• 1986

Net production, dead material increments were measured, and annual respiration loss was simulated through a year to determine the gross production at the Phragmites longivalvis, Carex scabrifolia and Zoysia sinica stand on Okryudeung, a sand bar of the Nagdong river estuary. The maximum live biomass for above-ground organs of the three stands occured in October, i.e., 1, 985, 744 and 1, 013g/m2, and belowground net productions were estimated to be 650, 440 and 412g/m2, respectively. Materials died or shedding from live aboveground organs during the growth season were estimated to be 167, 81 and 0 g/$m^2$. From the results of simulation, annual variation of respiratiion was primarily dependent on the annual variation of temperature through a year. For annual respiration loss in three stands, 21.893, 6.147 and 5.036kg $CO_2/m^2$ were calculated, respectively. Corresponding gross productions were 72, 203, 22, 109 and 19, 909kcal/$m^2$. Respiration of belowground organs corresponded to 65%, 66% and 37% of the total plant respiration, and annual respiration loss accounted for 85%, 78% and 71% of the annual gross production. In view of efficiency of solar energy utilization, 5.8%, 1.8% and 1.6% of incident light energy were converted to gross production of plants during a year. With incident light energy during the growth season from April to September, energy utilizations for net production were estimated to be 1.2%, 0.4% and 0.6% at the three stands.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.215-219
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• 2005

A macro spreadsheet model, WEANES (Wet Pond Annual Efficiency Simulation Model), has been developed to predict the long-term or annual removal efficiencies of wet retention/detention basins. The model uses historical, site-specific, multi-year, rainfall data, usually available from a nearby National Oceanic and Atmospheric Administration (NOAA) climatological station to estimate basin efficiencies which are calculated based on annual mass loads. Other required input parameters are: 1) watershed parameters; drainage area, pervious curve number, directly connected impervious area, and ti me of concentration, 2) pond parameters; control and overflow elevations, pond side slopes, surface areas at control elevation and pond bottom; 3) outlet structure parameters; 4) pollutant event mean concentrations; and 5) pond loss rate which is defined as the net loss due to evaporation, infiltration and water reuse. The model offers default options for parameters such as pollutant event mean concentrations and pond loss rate. The model can serve as a design, planning, and permitting tool for consulting engineers, planners and government regulators.

• Journal of Korean Society on Water Environment
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• v.25 no.1
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• pp.7-17
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• 2009

Soil and Water Assessment Tool (SWAT) was used to assess the impact of potential future climate change on the water cycle and soil loss of the Daecheong reservoir watershed. A sensitivity analysis using influence coefficient method was conducted for two selected hydrological input parameters and three selected sediment input parameters to identify the most to the least sensitive parameters. A further detailed sensitivity analysis was performed for the parameters: Manning coefficient for channel (Cn), evaporation (ESCO), and sediment concentration in lateral (LAT_SED), support practice factor (USLA_P). Calibration and verification of SWAT were performed on monthly basis for 1993~2006 and 1977~1991, respectively. The model efficiency index (EI) and coefficient of determination ($R^2$) computed for the monthly comparisons of runoffs were 0.78 and 0.76 for the calibration period, and 0.58 and 0.65 for the verification period. The results showed that the hydrological cycle in the watershed is very sensitive to climate factors. A doubling of atmospheric $CO_2$ concentrations was predicted to result in an average annual flow increase of 27.9% and annual sediment yield increase of 23.3%. Essentially linear impacts were predicted between two precipitation change scenarios of -20, and 20%, which resulted in average annual flow and sediment yield changes at Okcheon of -53.8%, 63.0% and -55.3%, 65.8%, respectively. An average annual flow increase of 46.3% and annual sediment yield increase of 36.4% was estimated for a constant humidity increase 5%. An average annual flow decrease of 9.6% and annual sediment yield increase of 216.4% was estimated for a constant temperature increase $4^{\circ}C$.