• Journal of the Korean GEO-environmental Society
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• v.21 no.4
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• pp.5-17
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• 2020

In recent years, the frequency of heavy rainfall associated with high rainfall intensity has been continuously increasing due to the effects of climate change; and thus also causes an increase in watershed soil erosion. The existing estimation techniques, used for the prediction of soil erosion in Korea have limitations in predicting the: average soil erosion in watersheds, and the soil erosion associated with abnormal short-term rainfall events. Therefore, it is necessary to consider the characteristics of torrential rainfall, and utilize physics-based model to accurately determine the soil erosion characteristics of a watershed. In this study, the rainfall kinetic energy equation, in the form of power function, is proposed by applying the probability density function, to analyze the rainfall particle distribution. The distributed rainfall-erosion model, which utilizes the proposed rainfall kinetic energy equation, was utilized in this study to determine the soil erosion associated with various typhoon events that occurred at Cheoncheon watershed. As a result, the model efficiency parameters of the model for NSE and RMSE are 0.036 and 4.995 ppm, respectively. Therefore, the suggested soil erosion model, coupled with the proposed rainfall-energy estimation, shows accurate results in predicting soil erosion in a watershed due to short-term rainfall events.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.153-160
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• 2020

The kinetic energy of the rain drops was predicted in a relation between the rain rate and rain quantity, derived directly from the rain drop size distribution (DSD), which had been measured by a disdrometer located in the eastern state of Alagoas-Brazil. The equation in the form of exponential form suppressed the effects of large drops at low rainfall intensity observed at the beginning and end of the rainfall. The kinetic energy of the raindrop was underestimated in almost rain intensity ranges and was considered acceptable by the performance indicators such as coefficient of determination, average absolute error, percent relative error, mean absolute error, root mean square error, Willmott's concordance index and confidence index.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.6
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• pp.55-69
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• 2016

RUSLE (Revised Universal Soil Loss Equation) is the empirical formular widely used to estimate rates of soil erosion caused by rainfall and associated overland flow. Among the factors considered in RUSLE, rainfall erosivity factor (R factor) is the major one derived by rainfall intensity and characteristics of rainfall event. There has been developed various methods to estimate R factor, such as energy based methods considering physical schemes of soil erosion and simple methods using the empirical relationship between soil erosion and annual total rainfall. This study is aimed to quantitatively evaluate the variation among the R factors estimated using different methods for South Korea. Station based observation (minutely rainfall data) were collected for 72 stations to investigate the characteristics of rainfall events over the country and similarity and differentness of R factors calculated by each method were compared in various ways. As results use of simple methods generally provided greater R factors comparing to those for energy based methods by 76 % on average and also overestimated the range of factors using different equations. The variation coefficient of annual R factors was calculated as 0.27 on average and the results significantly varied by the stations. Additionally the study demonstrated the rank of methods that would provide exclusive results comparing to others for each station. As it is difficult to find universal way to estimate R factors for specific regions, the efforts to validate and integrate various methods are required to improve the applicability and accuracy of soil erosion estimation.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.371-378
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• 2020

Rainfall is one of the most active forces that cause soil erosion. The action of rain on the soil exerts an erosive power caused by the impact of the drops, which fall with variable speed and kinetic energy, depending directly on the diameter of the drop. The objective of this study is to determine algorithms capable of estimating rainfall erosivity for the region of Maceió-AL. For this purpose, erosion rains were collected between 2003 and 2006 using a RD-69 disdrometer, which continuously and automatically measures rainfall distribution in a range of 1 min. The determination of algorithms in the form of power equation to estimate was adjusted with one and two independent variables (amount of rainfall, duration and maximum intensity).

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.129-129
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• 2022

국내에서 발생하는 토양침식(soil erosion)은 주로 강우에 의해 발생하며, 이로 인해 농경지 유실, 탁수 발생, 하천 통수능 저하 등 여러 수문학적·환경적 문제가 발생한다. 따라서 유역 내 토양침식 위험지역을 선별하고, 해당 지역의 토양유실 및 유사의 발생량을 산정하는 것은 토양보전 대책 수립 시에 중요한 지표로 활용된다. 침식-유사유출의 물리적 과정은 크게 '강우에 의한 토양 분리(detachment by raindrop)'와 '지표류에 의한 토양 분리(detachment by overlandflow)'로 나눌 수 있으며, 그중 강우에 의한 토양 분리는 수침식(water erosion)의 첫 번째 과정 중 하나로 강우 시 낙하하는 강우 입자들이 갖는 운동에너지가 지표면을 타격할 때 토양체로부터 토양입자가 분리되는 과정이다. 따라서 강우에 의한 토양분리량 산정을 위해서는 강우 운동에너지(rainfall kinetic energy, KE)의 정확한 계산이 요구된다. 그러나 기후 및 지리적 특성 등 여러 조건에 따라 강우 운동에너지는 지역마다 다르게 나타나며, 이로 인해 강우 운동에너지 추정이 매우 어려운 실정이다. 따라서 강우 운동에너지 추정은 주로 강우강도(rainfall intensity, I)와의 관계를 이용한 함수식을 활용한다. 본 연구에서는 대상 지역인 상주지역에 광학우적계(disdrometer)를 설치하여 2020년 6월부터 2021년 12월까지 관측된 37개의 강우 사상에 대하여 KE-I의 관계를 분석하고, 이를 통해 강우 운동에너지식을 도출하였다. 또한, 기존에 국외 및 국내에서 제시된 선형(linear), 멱함수(power-law function), 지수함수(exponential function) 형태의 강우 운동에너지 공식과 본 연구에서 산정된 KE를 비교하였다. 그 결과 비체적 강우 운동에너지에서 Sanchez-Moreno et al. (2012)가 제안한 멱함수 형태의 공식이, 비시간 강우 운동에너지에서 Kinnel (1981)이 제안한 지수함수 형태의 공식이 각각 강우 운동에너지 추정에 통계적으로 유의한 것으로 나타났다.

• 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.

• Korean Journal of Soil Science and Fertilizer
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• v.14 no.3
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• pp.104-109
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• 1981

The experiment was designed to measure splash erosion and to investigate the relationships between soil detachment, kinetic energy and C factor at various soils and crops under the natural rainfall, using the modified Ellison cup. The results obtained were as follows: 1. Splash erosion increased as the texture was coarser, reaching a maximum amount in loamy sand of 12.6ton/10a/year, 9.7ton for loam, 9.0ton for sandy loam, and 7.0ton for clay loam. 2. Splash erosion positively related to kinetic energy ($EI_{30}$) but negatively to K value. 3. A considerable relationship between splash erosion and kinetic energy was observed under coverage less than 50%; however, it decreased with increasing canopy resulting in no relation over 90% coverage. The amount of soil detachment by natural rainfall ranged from 10 to 15ton/10a at various cropping systems. 4. The particle size distribution of splashed soil was similar to that of original one and fine sand($250-100{\mu}$) marked the highest detachment and splash.

• Journal of information and communication convergence engineering
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• v.4 no.1
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• pp.46-52
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• 2006

Precipitation measurement with ground-based radar needs an information of the raindrop size distribution (RSD) characteristics. A 10-month dataset was collected in tropical Atlantic coastal zone of northeastern Brazil where the weather radar was installed. The number of drop was mainly recorded in 300 - 500 drop $mm^{-3}$, of which the maximum was registered around 1.1 mm drop diameter.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.130-145
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• 2016

Soil erosion processes are affected by weather factors, such as rainfall, temperature, wind, and humidity. Among these factors, rainfall directly influences soil erosion by breaking away soil particles. The kinetic energy of rainfall and water flow caused by rain entrains and transports soil particles downstream. Therefore, in order to estimate soil erosion, it is important to accurately determine the rainfall erosivity factor(R) in RUSLE(Revised Universal Soil Loss Equation). The objective of this study is to evaluate the average annual R using 14 years(2002~2015) of 1 minute rainfall data from 55 KMA(Korea Meteorological Administration) weather stations. The R results from 1 min rainfall were compared with previous R studies using 1 h rainfall data. The determination coefficients($R^2$) between R calculated using 1 min rainfall data and annual rainfall were 0.70-0.98. The estimation of 30 min rainfall intensity from 1 min rainfall data showed better $R^2$ results than results from 1 h rainfall data. For estimation of physical spatial rain erosivity(R), distribution of annual rainfall was estimated by IDW(Inverse Distance Weights) interpolation, taking elevation into consideration. Because of the computation burden, the R calculation process was programmed using the python GUI(Graphical User Interface) tool.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.543-552
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• 2020

This study is aimed at determining an algorithm capable of estimating the erosion index of rainfall for the region of Maceió-Alagoas in the northeast of Brazil. The sample of the truncated data from 2003 to 2006 counts 26,889 droplet size distributions integrated per minute, with 680 rain events with duration longer than 10 minutes. The equation proposed to estimate erosion index used as a dependent variable and independent variable, presenting a coefficient of determination of 99%. The statistical significance validated the relation between minimum rainfall intensity and erosion.