• 한국농공학회논문집
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• 제58권3호
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• pp.57-69
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• 2016

In this study, we analyzed the extreme rainfall distribution scenarios based on probable rainfall calculation and applying various time distribution models over the landslide high risk zones in urban areas. We used observed rainfall data form total 71 ASOS (Automated Synoptic Observing System) station and AWS (Automatic Weather Station) in KMA (Korea Meteorological Administration), and we analyzed the linear trends for 1-hr and 24-hr annual maximum rainfall series using simple linear regression method, which are identified their increasing trends with slopes of 0.035 and 0.660 during 1961-2014, respectively. The Gumbel distribution was applied to obtain the return period and probability precipitation for each duration. The IDF (Intensity-Duration-Frequency) curves for landslide high risk zones were derived by applying integrated probability precipitation intensity equation. Results from IDF analysis indicate that the probability precipitation varies from 31.4~38.3 % for 1 hr duration, and 33.0~47.9 % for 24 hr duration. It also showed different results for each area. The $Huff-4^{th}$ Quartile method as well as Mononobe distribution were selected as the rainfall distribution scenarios of landslide high risk zones. The results of this study can be used to provide boundary conditions for slope collapse analysis, to analyze sediment disaster risk, and to use as input data for risk prediction of debris flow.

• 한국농공학회지
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• 제36권3호
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• pp.122-134
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• 1994

The objective of this study is to provide with the hydrometeological and probabilistic characteristics of the storms and winds of typhoons that have been passed through the Korea peninsula during the last twenty-three years since 1961. The paths and intensities of the typhoons were analyzed. Fifty weather stations were selected and the rainfall and wind data during typhoon periods were collected. Rainfall data were analyzed for the patterns and probabilistic distributions. The results were presented to describe the areal distributions of probabilistic characteristics. Wind data were also analysed for their probabilistic distributions. The results obtained from this study can be summarized as follows: 1. The most frequent typhoon path that have passed through the Korean peninsula was type E, which was followed by types CWE, W, WE, and S. The most frequent typhoon intensity was type B, that was followed by A, super A, and C types, respectively. 2. The third quartile typhoon rainfall patterns appear most frequently followed by the second, first, and quartiles, respectively, in Seoul, Pusan, Taegu, Kwangju and Taejon. The single typhoon rainfalls with long rainfall durations tended to show delayed type rainfall patterns predominantly compared to the single rainfalls with short rainfall durations. 3. The most frequent probabilistic distribution for typhoon rainfall event is Pearson type-III, followed by Two-parameter lognormal distribution, and Type-I extremal distribution. 4. The most frequent probability distribution model of seashore location was Pearson type-III distribution. The most frequent probability distribution model of inland location was two parameter lognormal distribution. 5. The most frequent probabilistic distribution for typhoon wind events was Type-I xtremal distribution, followed by Two-parameter lognormal distribution, and Normal distribution.

• Current Research on Agriculture and Life Sciences
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• 제15권
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• pp.53-67
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• 1997

The objective of this study is to provide with the hydro-meteological and probabilistic characteristics of the storms of typhoons that have been passed through the Korean peninsula during the last twenty-three years since 1961. The paths and intensities of the typhoons were analyzed. Fifty weather stations were selected and the rainfall data during typhoon periods were collected. Rainfall data were analyzed for the patterns and probabilistic distributions. The results were presented to describe the areal distributions of probabilistic characteristics. The results obtained from this study can be summarized as follows: 1. The most frequent typhoon path that has passed through the Korean peninsula was type E, followed by types CWE, W, WE, and S. The most frequent typhoon intensity was type B, followed by A, super A, and e types, respectively. 2. The third quartile typhoon rainfall patterns appear most frequently followed by the second, first, and last quartiles, respectively, in Seoul, Pusan, Taegu, Kwangju and Taejon. The single typhoon rainfalls with long rainfall durations tended to show delayed type rainfall patterns predominantly compared to the single rainfalls with short rainfall durations. 3. The most frequent probabilistic distribution of typhoon rainfall event is Pearson type-III, followed by Two-parameter lognormal distribution, and Type-I extremal distribution. 4. The most frequent probability distribution model of seashore location was Pearson type-III distribution. The most frequent probability distribution model of inland location was two parameter lognormal distribution.

• 한국농공학회지
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• 제43권5호
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• pp.70-82
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• 2001

This study was conducted to derive the regional design rainfall by the regional frequency analysis based on the regionalization of the precipitation suggested by the first report of this project. Using the L-moment ratios and Kolmogorov-Smirnov test, the underlying regional probability distribution was identified to be the Generalized extreme value distribution among applied distributions. Regional and at-site parameters of the generalized extreme value distribution were estimated by the linear combination of the probability weighted moments, L-moment. The regional and at-site analysis for the design rainfall were tested by Monte Carlo simulation. Relative root-mean-square error(RRMSE), relative bias(RBIAS) and relative reduction(RR) in RRMSE were computed and compared with those resulting from at-site Monte Carlo simulation. All show that the regional analysis procedure can substantially reduce the RRMSE, RBIAS and RR in RRMSE in the prediction of design rainfall. Consequently, optimal design rainfalls following the legions and consecutive durations were derived by the regional frequency analysis.

• 상하수도학회지
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• 제24권5호
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• pp.509-517
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• 2010

Statistical distribution of annual maximum rainfall intensity of 18 cities in Korea was analyzed and applied to the reliability model which can calculate the probability of performance failure of storm sewer. After the analysis, it was found that distribution of annual maximum rainfall intensity of 18 cities in Korea is well matched with Gumbel distribution. Rational equation was used to estimate the load and Manning's equation was used to estimate the capacity in reliability function to calculate the probability of performance failure of storm sewer. Reliability analysis was performed by developed model applying to the real storm sewer. It was found that probability of performance failure is abruptly increased if the diameter is smaller than certain size. Therefore, cleaning the inside of storm sewer to maintain the original diameter can be one of the best ways to reduce the probability of performance failure. In the present study, probability of performance failure according to accumulation of debris in storm sewer was calculated. It was found that increasing the amount of debris seriously decrease the capacity of storm sewer and significantly increase the probability of performance failure.

• 한국방재학회 논문집
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• 제7권2호통권25호
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• pp.13-24
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• 2007

본 연구에서는 우리나라 강우에 다변량 분석기법을 적용하여 대표확률분포형을 결정하고, 결정된 대표확률분포형으로부터 확률강우강도식을 유도하였다. 강우자료는 30년 이상의 연최대강우자료로서 12개의 지속기간(10분, 1, 2, 3, 4, 5, 6, 8, 10, 12, 18, 24시간)과 50개의 강우특성인자를 적용하였다. 확률분포형은 빈도해석에 널리 사용되는 14개 분포형을 사용하였으며, 전 지역의 강우 동질성을 검정하는 방법으로 주성분분석과 군집분석을 실시하였다. 본 연구의 수행으로 얻어진 결과를 하면 다음과 같다. 첫째, 우리나라 전역을 대표할 수 있는 적정분포형을 선정할 수는 없었으나, 수문학적 동질성이 인정되는 5개의 권역으로 구분하였다. 둘째, I, III, IV, V 권역은 GEV 분포, I I권역은 Gumbel 분포가 대표적정분포형으로 선정되었다. 셋째, 대표적정분포형에 의한 확률강우량은 기존 연구들과 차이가 발생하는 것을 알 수 있었다. 넷째, 대표적정분포형으로부터 얻어진 확률강우량을 이용하여 대표확률강우강도식을 유도하였다.

• 한국수자원학회논문집
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• 제32권3호
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• pp.247-254
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• 1999

우리 나라 주요 우량관측소 22개 지점의 매년 최대치 강우자료에 대하여 빈도해석을 실시하였다. 매개변수 추정방법은 모멘트법, 확률가중 모멘트법, 최우도법 등이며, 매개변수 적합성, 도시적 해석, 분리효과, 적합도 검정결과 GEV 분포가 우리 나라 강우자료에 대하여 가장 적합한 확률분포형으로 나타났다. 선정된 GEV 분포형을 모집단의 확률분포형으로 가정하여 재현기간별 확률강우량을 산정하므로써 지역적 해석을 실시하였으며, 정확도 있는 선형화 기법을 통해 회귀분석을 실시하여 확률강두강도식을 유도하였다. 본 연구에서 유도된 확률강우강도식은 실무차원에서 임의 지속기간의 재현기간별 확률강우량을 간편하게 구할 수 있을 것으로 판단된다.

• 한국수자원학회논문집
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• 제42권10호
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• pp.857-866
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• 2009

본 연구에서는 전국의 30년 이상의 강우관측기록을 보유하고 있는 기상청 산하 56개 강우관측소의 연 최대치 강우자료들로부터 확률분포형에 대하여 모멘트법, 최우추정법, 확률가중모멘트법을 이용하여 모수를 추정하고, 그 모수의 범위와 확률변수의 범위에 대한 적정성을 알아보았다. 적정성이 있는 모수를 대상으로 적합도 검정법인 x$^2$-검정, K-S검정, Cramer von Mises (CVM)검정, Probability Plot Correlation Coefficient (PPCC) 검정을 실시한 결과 중, 최근 연구에서 많이 이용되고 있고 표본자료의 크기가 작거나 왜곡된 자료일 경우에도 비교적 안정적인 결과를 얻을 수 있는 확률가중모멘트법과 상관계수에 의한 검정인 PPCC검정을 통과한 분포형을 우선적으로 적합도 평가 대상 분포형으로 선정하였다. 선정된 분포형을 대상으로 적합도 평가기준인 SLSC, MLL, AIC를 적용하여 적합도 평가를 실시하여 대표확률분포형 후보군을 추출하였다. 대표확률분포형 후보군으로 선정된 확률분포형에 대하여 resampling방법인 Jackknife기법을 적용하여 변동성을 파악하고, 변동성이 가장 작게 나타난 분포형을 그 지점의 대표확률분포형으로 결정하였다. 본 논문에서는 분석 결과의 분량을 감안하여 대표적으로 서울, 강릉, 대구, 전주, 부산 지점에 대해 작성하였으며, 확률강우량의 변동성이 가장 작은 확률분포형을 56개 지점의 각 지점 대표확률분포형으로 제시하였으며, Gumbel 분포(GUM)의 선정 비율이 지속기간 12시간, 24시간에 대해 각각 41 %, 32 %로 가장 높게 나타났다. 본 연구에서는 적합도 평가를 함에 있어서 객관적 정량화가 가능한 세 가지 기준과 Jackknife기법을 이용한 새로운 확률분포형 선정의 가능성을 제시하였다.

• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.857-865
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• 2013

집중 호우로 인한 피해가 증가하면서 다양한 기법들을 이용하여 강우량 예측에 대한 관심이 높아졌다. 최근에는 극단분포를 활용하여 강우량을 예측하려는 시도가 늘고 있다. 본 연구에서는 일반화 극단 분포를 활용하여 실제 서울시의 1973년부터 2010년까지 7월달의 사후예측분포를 생성하고, 수치적인 계산을 위해서 MCMC (Markov chain Monte Carlo)알고리즘을 활용하였다. 이 연구를 통해서 사후예측분포의 점추정값들을 비교하였고 2011년 7월달의 자료와 비교해 봤을 때 집중 호우의 확률이 증가한 것을 알 수 있었다.

• 상하수도학회지
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• 제30권1호
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• pp.41-49
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• 2016

In this study, rainfall characteristics with stationary and non-stationary perspectives were analyzed using generalized extreme value (GEV) distribution and Gumbel distribution models with rainfall data collected in major cities of Korea to reevaluate the return period of sewer flooding in those cities. As a result, the probable rainfall for GEV and Gumbel distribution in non-stationary state both increased with time(t), compared to the stationary probable rainfall. Considering the reliability of ${\xi}_1$, a variable reflecting the increase of storm events due to climate change, the reliability of the rainfall duration for Seoul, Daegu, and Gwangju in the GEV distribution was over 90%, indicating that the probability of rainfall increase was high. As for the Gumbel distribution, Wonju, Daegu, and Gwangju showed the higher reliability while Daejeon showed the lower reliability than the other cities. In addition, application of the maximum annual rainfall change rate (${\xi}_1{\cdot}t$) to the location parameter made possible the prediction of return period by time, therefore leading to the evaluation of design recurrence interval.