• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.15-15
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• 2018

강우에 의해 발생되는 토양침식의 정도를 나타내는 강우침식인자의 산정공식은 미국에서 경험적인 방법으로 유도된 식이지만, 전 세계적으로 널리 활용되고 있다. 강우침식인자는 토양침식을 유발하는 호우사상의 지속기간 중에 발생한 총 강우에너지와 30분 최대 강우강도 값을 곱하여 호우사상별로 산정하게 되며, 이 값의 연간 총합이 연강우침식인자가 된다. 최근 강우침식인자에 대한 관심이 국내외적으로 고조되면서 많은 연구 산물이 학계에 보고되고 있다. 본 연구의 목적은 동일 기간, 동일 지점일지라도 연구자에 따라 강우침식인자 값이 달라지는 원인과 그 불확실성을 규명하기 위한 것이다. 이를 위하여 본 연구는 강우침식인자와 관련된 국내외 문헌연구를 토대로 연구방법에 따라 결과값이 달라지는 현상을 분석하고 이에 대한 대안을 제시하고자 한다. 연구결과, 강우침식인자 산정의 불확실성의 가장 큰 인자는 연구자가 사용하는 데이터로서, 5분 단위 이하의 강우자료를 사용하는 것과, 그 이상의 자료를 사용하는 것으로 구분할 수 있었다. 두 번째 중요한 인자는 유효 호우사상의 분류기준을 어떻게 적용하느냐에 있었다. 세 번째는 강우 에너지를 계산할 때 어떤 강우운동에너지식을 적용하는지에 따라 결과값이 달라지는 것을 알 수 있었다. 네 번째는 연구자가 어떤 프로그램을 이용하여 산정했느냐에 따라 차이가 발생할 수 있음을 알 수 있었다. 다섯 번째 지역단위 강우침식인자 산정시 어떤 공간분포 기법을 적용하느냐에 따라 결과값의 차이가 발생함을 알 수 있었다. 이를 바탕으로 본 연구에서는 국내에서 강우침식인자 산정시 연구자들이 적용할 수 있는 표준 계산 절차에 대해서 제안하였다.

• Journal of Soil and Groundwater Environment
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• v.24 no.5
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• pp.31-41
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• 2019

In 2013, the Ministry of Environment in South Korea promulgated a new regulatory bulletin that contained revised enforcement ordinance on soil management protocols. The bulletin recommends the use of Universal Soil Loss Equation (USLE) for the soil erosion estimation, but USLE has limited applicability in prediction of soil erosion because it does not allow direct estimation of actual mass of soil erosion. Therefore, there is a great need of revising the protocol to allow direct comparison between the measured and estimated values of soil erosion. The Korean Soil Loss Equation (KORSLE) was developed recently and used to estimate soil loss in two fields as an alternative to existing USLE model. KORSLE was applied to estimate monthly rainfall erosivity indices as well as temporal variation in potential soil loss. The estimated potential soil loss by KORSLE was adjusted with correction factor for direct comparison with measured soil erosion. The result was reasonable since Nash-Stucliff efficiency were 0.8020 in calibration and 0.5089 in validation. The results suggest that KORSLE is an appropriate model as an alternative to USLE to predict soil erosion at field scale.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.410-410
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• 2021

강우가식성 지표(또는 강우침식인자)는 빗방울이 지상으로 떨어질 때 빗방울의 크기와 낙하속도 즉 운동에너지에 의하여 표토의 입자가 잠재적으로 침식될 수 있는 정도를 의미한다. 최신 호우사상을 분석하여 지점별 연평균 강우가식성 지표를 지속적으로 갱신하는 연구는 범용토양유실공식을 이용하여 장기간에 걸친 연평균 토양침식량을 산정하려고 하는 연구자들에게 지속적인 관심의 대상이 되어 왔다. 본 연구는 기상청 산하 관측소 54개 지점을 대상으로 지점별 연평균 강우가식성 지표를 업데이트하기 위한 것으로, 2017년까지의 데이터를 포함하여 업데이트하는 것을 목표로 하였다. 강우 가식성 지표 계산을 위한 1분 단위 강우자료는 기상자료개방포털의 공개된 자료로부터 획득할 수 있으나, 지점별로 결측치를 일부 포함하고 있거나 불연속된 자료가 포함되어 있어 54개 지점 모두를 업데이트하는 것은 제한이 되었다. 결과적으로 54개 지점 중에 29개 지점에 대한 값을 업데이트할 수 있었다. 연구결과 기상청 29개 지점의 1961~2017년 기간(최소 45년 ~ 최대 57년) 동안의 연평균 강우가식성 지표는 4,624MJmm/ha/hr로 나타났다. 이 값은 2015년 기간까지의 평균값과 거의 차이가 없는 것으로 나타났다. 또한, 지역적 분포로서 29개 지점 중에 14개 지점에서 연평균 강우가식성 지표가 소폭 감소한 것으로 나타났으며, 15개 지점은 증가한 것으로 나타났으며 최대 증가 및 감소폭은 2.5% 이내인 것으로 나타났다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.412-412
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• 2021

일반적으로 강우자료의 시간 해상도가 높을수록(측정 주기가 짧아질수록) 강우침식능 값이 크게 산정되는 경향이 있다(Yin et al. 2015). 또한, 강우자료의 시간해상도가 서로 다를 경우에 각각 산정된 강우침식능 값을 동일한 값으로 비교하기 위해서는 어떤 변환 과정을 거쳐야 하는지에 대한 해석기법이 정립되어야 한다. 강우자료의 시간 해상도가 다를 경우 결과 값이 달라진다는 것은 알고 있지만, 이 값을 동일하게 산정된 값으로 간주하고 비교하는 것은 실무적으로 큰 오류를 범할 수 있다. 본 연구는 이러한 문제에 대하여 통계적인 방법과 강우의 스케일링 성질을 이용하여 서로 다른 지속기간을 갖는 해상도를 강우자료로 산정된 강우침식능 값을 상호 비교하여 변환할 수 있는 인자를 가진 실험식을 제시하고자 한다. 지난 50여 년 동안 전 세계 많은 연구자들이 서로 다른 방법으로 다양한 강우침식능 값을 산정하고 제시하였으나, 국가별로 상이한 자료와 각기 다른 계산방법으로 산정한 값을 동일한 값으로 비교하는 것은 큰 오류가 있으며, 이러한 오류를 감소시키기 위해서는 강우침식인자 계산방법에 대한 적절한 기준을 통한 산정방법이 마련되어야 한다. 본 연구를 통해 강우자료의 다양한 시간해상도에 따른 강우침식능 추정기법이 정립되면, 국내외 학계 및 실무자들이 각기 다양한 시간해상도로 산출된 강우침식능을 비교 분석할 수 있는 밑바탕을 마련할 수 있을 것으로 판단된다.

• Spatial Information Research
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• v.17 no.3
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• pp.261-268
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• 2009

This study accomplished to draw a soil erosion map and a grade map of soil loss hazard in Korea. RUSLE and Rainfall-runoff (R) factor, which was estimated by using the rainfall data observed in 59 meteorological stations from 1977 to 2006 (for 30 years). FARD was used to analyze the frequency, and the whole country R factor was estimated according to the frequency. In the analysis of estimating the whole country R factor, Nakdong river has the smallest vaule, but Han river has the biggest value. According to the result of analyzing soil loss, soil loss occurred in a grass land, a bare land and a field in size order, and also approximately 17.2 ton/ha soil loss happened on the whole area. The average soil loss amount by the unit area takes place in a bare land and a grass land a lot. The total amount of soil loss in 5-year-frequency rainfall yields 15,000 ton and, what is more, a lot of soil loss happens in a paddy field, a forest and a crop field. The grade map of soil loss hazard is drawn up by classifying soil loss hazard grade by 5. As a result of analyzing soil loss, the moderate area which is the soil loss hazard grade 2 takes up the largest part, 72.8% of the total soil loss hazard area, on the contrary, the severe soil loss hazard area takes up only $1,038km^2$ (1.1%) of the whole area. The severe soil loss hazard area by land cover shows $93.5km^2$ in a bare land, $168.1km^2$ in a grass land and $327.4km^2$ in a crop field respectively.

• Journal of Korean Society on Water Environment
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• v.26 no.5
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• pp.841-849
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• 2010

Soil erosion is an natural phenomenon. However accelerated soil erosion has caused many environmental problems. To reduce soil loss from a watershed, many management practices have been proposed worldwide. To develop proper and efficient soil erosion best management practices, soil erosion rates should be estimated spatially and temporarily. The Universal Soil Loss Equation (USLE) and USLE-based soil erosion and sediment modelling systems have been developed and tested in many countries. The Sediment Assessment Tool for Effective Erosion Control (SATEEC) system has been developed and enhanced to provide ease-of-use interface to the USLE users. However many researchers and decision makers have requested to enhance the SATEEC system for simulation of soil erosion and sediment reflecting effects of single storm event. Thus, the SATEEC R factors were estimated based on 5 day antecedent rainfall data. The SATEEC 2.1 daily R factor was applied to the study watershed and it was found that the R2 and EI values (0.776 and 0.776 for calibration and 0.927 and 0.911 for validation) with the daily R were greater than those (0.721 and 0.720 for calibration and 0.906 and 0.881 for validation) with monthly R, which was available in the SATEEC 2.0 system. As shown in this study, the SATEEC with daily R can be used to estimate soil erosion and sediment yield at a watershed scale with higher accuracy. Thus the SATEEC with daily R can be efficiently used to develop site-specific soil erosion best management practices based on spatial and temporal analysis of soil erosion and sediment yield at a daily-time step, which was not possible with USLE-based soil erosion modeling system.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.291-300
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• 2022

Artificial disturbance in mountainous areas increases the sensitivity to erosion by exposure of the subsoil with a low loam ratio to the surface. In this study, rainfall simulations were conducted to evaluate the erodibility of sand and loamy sand in the interrill erosion by the rainfall-induced sheet flow. The mean diameters of sand and loamy sand used in the experiment were 0.936 mm and 0.611 mm, respectively, and the organic matter content was 2.0% and 4.2%, respectively. In the experimental plot, the runoff coefficient of overland flow increased 1.16 times in loamy sand rather than sand. Mean sediment yields of loamy sand and sand by sheet erosion were 3.71kg/m²/hr and 1.13kg/m²/hr respectively. The erodibility, the rate of soil erosion for rainfall erosivity factor, was 3.65 times greater in loamy sand than in sand. As the gradient of the steep slope increased from 24° to 28°, the sediment concentration and the erodibility for two soils increased by about 20%. The erodibility factor K of sandy soils for small plots was overestimated compared to the measured erodibility. This means that RUSLE can overestimate the sediment yields by sheet erosion on sandy soils.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.1
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• pp.121-130
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• 1993

The major objective of this study is to develop practical methods for estimating sediment yield rates of medium size watersheds of which areas range from 200 to $2,000km^2$. For this purpose, this study adopts an empirical method of statistical approach and another empirical method of weighting the watershed characteristics factors. A total of 13 data points for sediment yield rate, including five data points from reservoir deposit data and eight data points from sampled river-sediment data have been collected. Meanwhile, seven factors that may affect the sediment yield rate of a watershed have been selected. They are drainage density, rainfall erosivity, ground cover and land use, soil erodibility, topography, river-bed material characteristics, and watershed area. In the companion paper following this paper, methods for estimating sediment yield rate are to be developed using the 13 data points collected and seven watershed characteristics factors selected in this study.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.37-44
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• 2018

Universal soil loss equation (USLE) had been employed to estimate potential soil loss since it was developed from the statewide data measured and collected in the United States. The equation had an origin in average annual soil loss estimation though, it was modified or improved to provide better opportunities of soil loss estimation outside the United States. The equation has five factors, most studies modifying them to adapt regional status were focused on rainfall erosivity factor and cover management factor. While the conservation practice factor (USLE P factor) is to represent distinct features in agricultural fields, it is challenging to find studies regarding the factor improvements. Moreover, the factor is typically defined using slopes. The factor defining approach was suggested in the study, the approach is a step-by-step method allowing USLE P factor definition with given condition. The minimum condition is slope and field location to provide an opportunity for using in any GIS software and to reflect regionally distinct features. If watershed location, slope, crop type, and mulching type on furrows are given, detailed definition of the factors are possible. The approach was developed from field survey in South-Korea, it is expected to be used for potential soil loss using USLE in South-Korea.

• Spatial Information Research
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• v.3 no.1
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• pp.1-18
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• 1995

Despite the widespread use of GIS over the past ten years, it has been limited application for regional modeling of pollutant loadings such as sediment, nitrogen, and phosphorus(non-point source pollution), The goals of this study were to: select important processes and parameters of watersheds that contribute to non-point source pollution degradation, develop a ranking model to use the environmental geologic data and verify the model by comparing results with existing water quality data(Chung-ju Lake) for specific watersheds, The GIS database consisted of topography, geology, soils, precipitation, rainfall erosivity, land use, and watershed boundaries. The index(NPSP) for assessing non-point source pollution was comprised in the following three seperate components: soil loss index(SLI) assesses the potential soil erosion and sedim-ent delivery from field to stream; run-off potential ratio(R.P.R) predicts the potential production of surface runoff; chloropgyll-a index ranks the potential manure(animal or human) production within a watershed. The GIS model was a valuable tool to assess the impact of environmental pollation in watersheds.