• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.260-260
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• 2016

Soil erosion is a very serious problem from agricultural as well as environmental point of view. Various computer models have been used to estimate soil erosion and assess erosion control practice. Universal Soil loss equation (USLE) is a popular model which has been used in many countries around the world. Erosivity (USLE R-factor) is one of the USLE input parameters to reflect impacts of rainfall in computing soil loss. Value of R factor depends upon Energy (E) and maximum rainfall intensity of specific period ($I30_{max}$) of that rainfall event and thus can be calculated using higher temporal resolution rainfall data such as 10 minute interval. But 10 minute interval rainfall data may not be available in every part of the world. In that case we can use hourly rainfall data to compute this R factor. Maximum 60 minute rainfall ($I60_{max}$) can be used instead of maximum 30 minute rainfall ($I30_{max}$) as suggested by USLE manual. But the value of Average annual R factor computed using hourly rainfall data needs some correction factor so that it can be used in USLE model. The objective of our study are to derive relation between averages annual R factor values using 10 minute interval and hourly rainfall data and to determine correction coefficient for R factor using hourly Rainfall data.75 weather stations of Korea were selected for our study. Ten minute interval rainfall data for these stations were obtained from Korea Meteorological Administration (KMA) and these data were changed to hourly rainfall data. R factor and $I60_{max}$ obtained from hourly rainfall data were compared with R factor and $I30_{max}$ obtained from 10 minute interval data. Linear relation between Average annual R factor obtained from 10 minute interval rainfall and from hourly data was derived with $R^2=0.69$. Correction coefficient was developed for the R factor calculated using hourly rainfall data.. Similarly, the relation was obtained between event wise $I30_{max}$ and $I60_{max}$ with higher $R^2$ value of 0.91. Thus $I30_{max}$ can be estimated from I60max with higher accuracy and thus the hourly rainfall data can be used to determine R factor more precisely by multiplying Energy of each rainfall event with this corrected $I60_{max}$.

• 한국농공학회지
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• 제45권3호
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• pp.29-40
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• 2003

The objective of the paper is to compute the half-month rainfall-runoff erosivity factor for revised universal soil loss equation (RUSLE). RUSLE is being used to develop soil conservation programs and identify optimum management practices. Rainfall-runoff erosivity factor (R) is a key input parameter to RUSLE. Rainfall-runoff erosivity factor has been calculated for twenty six stations from the nationwide rainfall data from 1973 to 2002 in south Korea. The average annual Rainfall-runoff erosivity factor at the analyzed stations Is between 3,130 and 10,476 (MJ/ha)ㆍ(mm/h). According to the computation of the half-month Rainfall-runoff erosivity factor for locations, 66-85% of the average annual R value has occurred during the summer months, June-August. The half-month R values from this study can be used for RUSLE.

• 한국콘텐츠학회논문지
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• 제15권3호
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• pp.406-414
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• 2015

기존 교통량 관련 연구는 기상이 양호한 상태에서 진행하였거나 기상에 대한 영향을 제외한 경우가 대부분이다. 이에 본 연구에서는 강우 강도 따른 일반국도 지방부 지역에서 교통량 변동 특성 및 강우 보정계수를 제시하였다. 일반국도 상시 교통량 조사지점과 자동기상관측 장비 지점을 매칭한 후 지방부 도로에 설치된 256 지점을 선정하여 분석하였다. 평균 일교통량(ADT: Average Daily Traffic) 및 강우 보정계수의 분석결과 평일의 경우 업무통행으로 인하여 강우의 영향을 적게 받으며, 비평일의 경우 여가통행으로 강우의 영향을 상대적으로 많이 받는 것으로 나타났다. 강우 보정계수를 적용하여 연평균 일교통량(AADT: Annual Average Daily Traffic) 추정 시 오차율이 줄어드는 것으로 분석되어 AADT 추정 시 강우에 대한 고려가 필요하다. 강우는 평균 일교통량을 감소시키는 요인으로 작용함에 따라 도로의 설계 및 운영을 위해 강우 강도를 고려한 지속적인 연구가 필요하다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.427-427
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• 2015

The storm water management and drainage relation are the key variable that plays a vital role on hydrological design and risk analysis. These require knowledge about spatial variability over a specified area. Generally, design rainfall values are expressed from the fixed point rainfall, which is depth at a specific location. Concurrently, determine the areal rainfall amount is also very important. Therefore, a spatial rainfall interpolation (point rainfall converting to areal rainfall) can be solved by areal reduction factor (ARF) estimation. In mainland of South Korea, for dam design and its operation, public safety, other surface water projects concerned about ARF for extreme hydrological events. In spite of the long term average rainfall (2,061 mm) and increasing extreme rainfall events, ARF estimation is also essential for Jeju Island's water control structures. To meet up this purpose, five fixed rainfall stations of automatic weather stations (AWS) near the "Hancheon Stream Watershed" area has been considered and more than 50 years of high quality rainfall data have been analyzed for estimating design rainfall. The relationship approach for the 24 hour design storm is assessed based on ARF. Furthermore, this presentation will provide an outline of ARF standards that can be used to assist the decision makers and water resources engineers for other streams of Jeju Island.

• 한국농공학회논문집
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• 제57권4호
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• pp.135-141
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• 2015

The objective of this study is to develop an early warning system for rainfall induced landslides. For this study, we suggested an analysis process using rainfall forecast data. 1) For a selected slope, safety factor with saturated depth was analyzed and safety factor threshold was established (warning FS threshold=1.3, alarm FS threshold=1.1). 2) If rainfall started, saturated depth and safety factor was calculated with rainfall forecast data, 3) And every hour after safety factor is compared with threshold, then warning or alarm can issued. In the future, we plan to make a early warning system combined with the in-situ inclinometer sensors.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2003년도 봄 학술발표회 논문집
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• pp.509-512
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• 2003

Our country is serious difference of precipitation seasonally and about 66% of yearly mean rainfall is happening in concentration rainfall form between September on June. It requires consideration because of a lot of natural disasters by this downpour are produced. Slope failure is happened by artificial factor of creation of slope according to the land development, fill slope etc. and natural factor of rainfall, topography, nature of soil, soil quality, rock floor. Usually, Direct factor of failure slope is downpour. In this study, the Slope about among 55 places happened failure by downpour investigated occurrence position, geological etc and executed and inquire into character of rainfall connected with failure slope. Among character of rainfall, executed analysis about Max. hourly rainfall and cumulative rainfall of place that failure slope is situated and grasped the geological character of failure slope. Through this, inquire to character of failure slope by rainfall and take advantage of basis study for Hazard map creation.

• 한국농공학회논문집
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• 제58권6호
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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.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2002년도 추계학술대회 논문집(I)
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• pp.601-607
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• 2002

Infiltration of rainfall causes railway embankment to be unstable and may result in failure. Basic relationship between the stability of railway embankment and rainfall introducing the partial saturation concept of ground are defined to analyze the stability of embankment by rainfall. A pressure plate test is also peformed to obtain soil-water characteristic curve of unsaturated soils. Based on this curve, the variables in the shear strength function and permeability function are also defined. These functions are used fur the numerical model for evaluation of railway embankments under rainfall. As comparing the model and case studies, the variation of shear strength, the degree of saturation and pore-water pressure for railway embankment during rainfall can be predicted and the safety factor of railway embankment can be expressed as the function of rainfall amount namely rainfall index. Therefore, the research on safety factor on railway embankment considering train speed and rainfall infiltration with the variation of rainfall intensity and rainfall duration was carried out in this paper.

• 한국농공학회논문집
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• 제60권6호
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• pp.13-20
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• 2018

Universal Soil Loss Equation (USLE) has been widely used to estimate potential soil loss because USLE is a simple and reliable method. The rainfall erosivity factor (R factor) explains rainfall characteristics. R factors, cited in the Bulletin on the Survey of the Erosion of Topsoil of the Ministry of Environment in the Republic of Korea, are too outdated to represent current rainfall patterns in the Republic of Korea. Rainfall datasets at one minute intervals from 2013 to 2017 were collected from fifty rainfall gauge stations to update R factors considering current rainfall condition. The updated R factors in this study were compared to the previous R factors which were calculated using the data from 1973 to 1996. The coefficient of determination between the updated and the previous R factors shows 0.374, which means the correlation is not significant. Therefore, it was concluded that the previous R factors might not explain current rainfall conditions. The other remarkable result was that regression equations using annual rainfall data might be inappropriate to estimate reasonable R factors because the correlation between annual rainfall and the R factors was generally unsatisfy.

• 한국토양비료학회지
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• 제16권2호
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• pp.112-118
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• 1983

전국 51개(個) 측후소(測候所) 및 분실(分室)의 강우성적(降雨成績)을 이용(利用)하여 토양유실량을 여측(予測)하기 위한 강우인자(降雨因子)(R-factor)를 분석(分析) 검토(檢討)한 결과(結果) 조사지역(調査地域)의 연평균(年平均) R-치(値)는 438이었으며 일반적(一般的)으로 동부지역(東部地域)은 R-치(値)가 200~300으로 낮았고 서부(西部) 및 남부지역(南部地域)과 제주도에서는 300~700으로 높았다. R-치(値)와 강우량(降雨量)과의 관계)는 지수함수의 유의성(有意性)있는 상관이 있었으며 이 관계식을 이용(利用)해 R-치(値)를 추정(推定)할 수 있었다. 포장(圃場)에서 측정(測定)한 토양유실량과 토양유실여측공식에 의(依)해 계산(計算)된 토양유실량을 비교(比較)해 본 결과(結果) 강우인자(降雨因子)는 EI 30을 사용(使用)하는 것이 타당(妥當)하였다.