• 물과 미래
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• 제19권3호
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• pp.249-258
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• 1986

본 연구는 수공구조물의 계획설계와 물관리 계획시 계획강우량의 결정기준이 되는 우리나라 전역의 최대하강수량 추정을 위한 최대하강수량 빈도계수 산정에 관한 내용이다. PMP 빈도계수 산정에 있어서는 연속기록년 20년의 자기우량기록지 보유지점을 대상으로 하였으며, 지속기간별(10분, 1,2,4,6,12,24시간) 연최대치 강우자료집단을 이용하여 연최대평균강우량에 따른 PMP 빈도계수를 결정할 수 있는 상관도를 작성하였다. 최대하강수량은 최대평균강우량과 빈도계수 및 지속기간 상관도상에서 얻어진 PMP 빈도계수와 통계치를 사용하여 통계학적 방법으로 산정하였으며, 포락선에 의해서 지점 최대하강수량과 지속기간 관계식을 유도하여 산정하였다. 산정된 지점 최대하강수량으로부터 전국에 대한 24시간 최대하강수량 분포도와 PMP·DAD 곡선을 작성하였다. ^ The purpose of this study is to estimate the PMP frequency factor for evaluation of the Probable Maximum Precipitation (PMP) in Korea. The value of PMP is the criterion of the determination of design rainfall in Planning and designing hydraulic structures, and water resources management. To obtain the object, 12 key stations were selected in which have the automatic rain0recording paper of 20 years, and the annual maximum rainfall values were calculated for each 7 durations(10 min., 1,2,4,6,12,24 hr.). The statistics(mean, standard deviation)were estimated, and diagram which shows the relationship between mean annual maximum rainfall($$) and frequency factor for each durations were drawn. PMP was estimated by statistical method using the PMP frequency factor obtained from the diagram and statistics($$, Sn). The PMP-Duration Equation was derived from the envelope curve in order to obtain the PMP for an arbitrary duration. The isohyetal map of 24 hours PMP and PMP. DAD curve for the whole of Korea were drawn in accordance with the point PMP values.

• 한국수자원학회논문집
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• 제49권12호
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• pp.995-1006
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• 2016

IPCC 제5차 평가보고서에 따르면 극한강우의 빈도 및 강도가 증가할 가능성이 매우 높을 것으로 예측되고 있다. 실제로 극한강우에 따른 침수피해가 증가하고 있으며, 이에 따라 기후변화의 영향을 반영한 미래 확률강우량 추정이 필요하다. 본 연구에서는 기후변화 RCP 8.5 시나리오로부터 도출된 미래 연 최대 일강수량 자료의 추세분석과 scale-invariance 기법을 이용하여 미래 확률강우량을 추정하였다. 먼저, 기상청 관할 60개 기상관측소의 관측 강우자료를 이용하여 관측소별로 스케일 특성을 검토한 후, 현재기후 모의자료를 이용하여 scale-invariance 기법의 적용가능성을 검증하였다. 그 후, 미래 일 강수량 시계열을 scale-invariance 특성에 따라 유도된 IDF 곡선식에 적용하여 기후변화의 영향을 반영한 지속시간별 확률강우량을 추정하였다. 대부분의 지점에서 확률강우량이 증가할 것으로 예측되었으나, 일부 지역의 경우에는 감소할 가능성도 있음을 살펴볼 수 있다.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2000년도 학술발표회 발표논문집
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• pp.397-404
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• 2000

A total of 65 rain gauges with Automatic Weather Station(AWS) were used to regional analysis of precipitation. Nine cluster regions were identified using geographical locations, maximum, mean, standard deviation of 1 day maximum rainfalls, mean annual precipitation and rainfall of rainy season in Korea. The mean annual precipitation, geographical locations, and the synoptic generating mechanisms were used to identify th five climatological homogeneous regions in Korea. Number of final regions by mean annual precipitation and cluster methods divided into five regions in Korea.

• 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 $I60_{max}$.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2000년도 학술발표회 발표논문집
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• pp.120-125
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• 2000

This study analyzes agricultural water demand nationwide which calculated by the estimation system for agricultural water demand(ESAD) with the data are observed in the other Studies. The results are as follows. Maximum, minimum and average values of annual evapotranspiration in paddy in 1,767 boundaries covering all the country are estimated as 819.2mm, 595.2mm and 702.9mm respectively. In the case of transplant seeding, the annual effective rainfall is estimated as 834.7mm to 464.3mm, while the average is 635.3mm. The amount of effective rainfall is largest in case of transplant seedlings and then come watered direct seeding and dry direct seeding regardless of region. Maximum, minimum and average values of annual evapotranspiration in upland in 1,767 boundaries are estimated as 659.97mm, 129.3mm and 411.8mm respectively. The annual effective rainfall is estimated as 607.2mm to 68.3mm while the average is 257.4mm. infiltration ratio in paddy in 1,767 boundaries applied in ESAD is 5.06mm/day in average, varying from 12.0mm/day to 2.0mm/day. Applied conveyance loss is 12.8% in average, varying from 18.0% to 8.0%.

• Current Research on Agriculture and Life Sciences
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• 제5권
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• pp.143-157
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• 1987

In order to determine the design precipitation, the most probable daily precipitation and annual precipitation at every spot are calculated and iso - precipitation line are drawn. Probability of precipitation and drought phenomena of each gage station are analyzied by the method of frequency analysis from the statistical conceptions. The results summarized in this study are as the follows. 1. Annual mean precipitation in kyungpook area are 1044 mm, about 115 mm less than annual mean precipitation of Korea amounts to l1S9mm, and found to regionally unequal. 2. Monthly mean rainfall of July is 242.2mm, 23.2%, August 174.2mm, 16.7%, June 115mm, 11% and September 114.2mm, 10.9% and Rainfall depth of July-August are more than 40% of annual precipition. This shows notable summer rainy weather by typoon and low pressure storm and seasonal unbalance of water supply. 3. The relation among the maximum precipi.tation per day, per two continuous days and per three contnous days are caculated and the latter is found 31.0% increased rate of the first and the last 48.2% increased rate of first. 4. Probability precipitation in Kyungpook area are shown as 9.0%(5 year), 13.3%(10 year), 17.7%(20 year), 23.1%(50 year), 27.0%(100 year) and 31.1%(200 year) increased rate of each recurrence year compared with observed average annual precipitation. 5. From annual precipitation and maximum daily rainfall data probability of precipitation and precipitation isohyetal line are derived which shown as Table 11 and Fig. 8. 6. Drought days are divided 6 class and analysed results are shown on table 12. Average occurrence time of 10-14 continuous drought days are 2.3 time per year, 15-19 days are 0.9 time per year, 20-24 days are one per six years, 30-34 days are once per nine years and over than 35days are once per 25 years.

• 한국토양비료학회지
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• 제44권3호
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• pp.337-343
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• 2011

A particular empirical equation for rainfall kinetic energy is needed to compute rainfall erosivity, calculated by the annual sum of the product of total rainfall energy and maximum 30-min rainfall intensity. If rainfall kinetic energy equation was different, rainfall erosivity will be produced differently. However, the previous studies in Korea had little concern about rainfall kinetic energy equation and it was not clear which rainfall kinetic energy is suitable for Korea. The purpose of this study is to analyze and evaluate the difference of the rainfall erosivity based on different rainfall kinetic energy equations obtained from previous studies. This study introduced new rainfall erosivity factors based on rainfall kinetic energy equation of Noe and Kwon (1984) that is only regression model developed in Korea. Data of annual rainfall erosivity for 21 weather stations in 1980~1999 were used in this study. The result showed that rainfall erosivity factors by the previous equations had been about 10~20% overestimated than rainfall erosivity by Noe and Kwon (1984)'s equation in Korea.

• 대한토목학회논문집
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• 제34권2호
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• pp.469-478
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• 2014

확률수문량을 산정하기 위해서 실무에서 많이 사용하는 연최대치 계열은 자료의 구축이 간편한 장점이 있지만, 우리나라에서 연최대치 계열을 이용하기에는 자료의 수가 매우 제한적이다. 특히, 적은 관측자료를 바탕으로 확률강우량 또는 설계홍수량을 추정할 경우 과다산정을 할 가능성이 매우 높다. 본 연구에서는 기상청에서 제공하는 1973년부터 2012년까지 총 40년간의 관측자료를 대상으로 독립호우사상을 구분하고, 연최대치 계열과 비연초과치 계열을 구성한 후, 연최대치 계열과 비연초과치 계열로부터 산정된 확률강우량의 상관성을 분석하고, 적은 관측자료를 가지고 지점빈도해석을 수행하여 확률강우량을 추정할 수 있는 방법을 제안하였다.

• 한국수자원학회논문집
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• 제38권10호
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• pp.885-894
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• 2005

1970년대 이후, 우리나라는 산업화에 따른 급격한 도시화가 이루어졌다. 본 논문에서는 우리나라의 대표적인 도시인 서울특별시 및 6대 광역시의 1973년부터 2003년까지의 31개년의 강수랑 자료를 이용하여 강수량의 변화에 대하여 분석하였다. 이와 함께 도시화에 따른 강수량의 변동성을 평가하기 위해서 비도시 지역을 선정하였으며 도시 지역의 강수량 변화와 비교하였다. 도시 지역과 비도시 지역의 연강수량, 계절별 강수량, 지속 시간 1시간 및 24시간연최대 강수량에 대해 임의기간에 따른 평균 분석, 경향성 분석, 변동성 분석, 비매개변수적 빈도 해석을 수행한 결과, 도시화 지역에서 비도시화 지역보다 강우 증가율이 더 컸으며, 특히 여름 강수량의 증가량이 두드러졌다.

• 물과 미래
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• 제17권2호
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• pp.99-106
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• 1984

우리나라의 12개 주요측후소-서울, 인천, 전주, 광주, 목포, 제주, 여수, 대구, 부산, 포항, 마산, 울릉도의 이용가능한 년최극 일강수량, 기온 및 기압관측치로부터 최극치의 빈도분포를 추정하였다. 첫 단계로 Jenkinson방법에 의한 극치확률을 추정하는 방법이 이용되었다. 추정결과는 재현년수에 대한 각 측후소의 일강수량, 기온 및 기압을 제시하는 그래프형태로서 제시되었으며 빈도분포형태가 토의되었다.