• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.97-97
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• 2018

기후변화로 악화되는 수문기상 환경에서 돌발홍수 예보, 짧은 지속기간(5분)의 확률강우량 생산 등을 위해서는 짧은 관측 주기의 강수량 생산 고려 필요하다. 지상강수량은 1분 간격으로 생산(기상청)하고 있으나 공간적으로 보다 정밀한 레이더 강수량은 기상청 10분, 국토교통부 2.5분 간격으로 생산하고 있는 현실이다. 연속으로 누적하여 강수량을 측정하는 강수량계와는 달리 레이더의 관측방식은 순간 관측 방식으로 회전 속도 혹은 주기에 따라 강수량이 달라질 수 있다. 특히 홍수예보를 위한 강수관측이 주목적인 국토교통부 강우레이더의 경우 최근의 돌발홍수 발생 빈도가 높아짐에 따라 초단시간(2분 이내) 강수량 생산의 필요성도 대두되고 있다. 따라서 본 연구에서는 관측 주기에 따른 관측 강수량 오차(불확실도) 분석을 실시하였다. 이를 위해 샘플링 방법을 이용하여 10분까지의 레이더 관측주기에 따른 1시간 누적강수량을 산정하고, 이를 이용하여 관측 주기에 따른 지상강수량계(AWS)와의 상관계수(correlation coefficient) 및 정규화오차 정확도(1-NE)를 분석하였다. 분석결과 샘플링 주기의 증가에 따라 오차가 증가하는 것으로 나타나, 강수량 추정의 정확도가 중요한 홍수예보를 위해서는 짧은 주기의 관측(짧은 주기의 강우량 생산)이 정확도 확보 측면에서 유리할 것으로 사료된다.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.775-784
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• 2022

In this study, to determine the optimal order of the full-logged I-D-F polynomial equation, which is mainly used to calculate the probable rainfall over a temporal rainfall duration, the probable rainfall was calculated and the regression coefficients of the full-logged I-D-F polynomial equation was estimated. The optimal variable of the polynomial equation for each station was selected using a stepwise selection method, and statistical significance tests were performed through ANOVA. Using these results, the statistically appropriately calculated rainfall intensity equation for each station was presented. As a result of analyzing the variable selection outputs of the full-logged I-D-F polynomial equation at 9 stations in Gyeongbuk, the 1^st to 3^rd order equations at 6 stations and the incomplete 3^rd order at 1 station were determined as the optimal equations. Since the 1^st order equation is similar to the Sherman type equation and the 2^nd order one is similar to the general type equation, it was presented as a unified form of rainfall intensity equation for convenience of use by increasing the number of independent variables. Therefore, it is judged that there is no statistical problem in considering only the 3^rd order polynomial regression equation for the full-logged I-D-F.

• Journal of Korea Water Resources Association
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• v.48 no.1
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• pp.37-44
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• 2015

A Bayesian nonstationary probability rainfall estimation model using the Grid method is developed. A hierarchical Bayesian framework is consisted with prior and hyper-prior distributions associated with parameters of the Gumbel distribution which is selected for rainfall extreme data. In this study, the Grid method is adopted instead of the Matropolis Hastings algorithm for random number generation since it has advantage that it can provide a thorough sampling of parameter space. This method is good for situations where the best-fit parameter values are not easily inferred a priori, and where there is a high probability of false minima. The developed model was applied to estimated target year probability rainfall using hourly rainfall data of Seoul station from 1973 to 2012. Results demonstrated that the target year estimate using nonstationary assumption is about 5~8% larger than the estimate using stationary assumption.

• Journal of Korea Water Resources Association
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• v.40 no.11
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• pp.851-859
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• 2007

In this study, the chukwookee data were evaluated by applying that for the historical rainfall frequency analysis. To derive a two parameter log-normal distribution by using historical data and modem data, censored data MLE and binomial censored data MLE were applied. As a result, we found that both average and standard deviation were all estimated smaller with chukwookee data then those with only modern data. This indicates that rather big events rarely happens during the period of chukwookee data then during the modern period. The frequency analysis results using the parameters estimated were also similar to those expected. The point to be noticed is that the rainfall quantiles estimated by both methods were similar. This result indicates that the historical document records like the annals of Chosun dynasty could be valuable and effective for the frequency analysis. This also means the extension of data available for frequency analysis.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.857-865
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• 2013

Extreme rainfall causes heavy losses in human life and properties. Hence many works have been done to predict extreme rainfall by using extreme value distributions. In this study, we use a generalized extreme value distribution to derive the posterior predictive density with hierarchical Bayesian approach based on the data of Seoul area from 1973 to 2010. It becomes clear that the probability of the extreme rainfall is increasing for last 20 years in Seoul area and the model proposed works relatively well for both point prediction and predictive interval approach.

• Journal of Korea Water Resources Association
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• v.32 no.3
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• pp.265-279
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• 1999

In this study, one of the techniques on the extension of low flow series has been developed, in which the daily streamflows were simulated by the Tank model with the input of extended daily rainfall series which were stochastically generated by the Markov chain model. The annual lowest flow serried for each of the given durations were formulated form the simulated daily streamflow sequences. The frequency of the estimated annual lowest flow series was analyzed. The distribution types to be used for the frequency analysis were two-parameter and three-parameter log-normal distribution, two-parameter and three-parameter Gamma distribution, three-parameter log-Gamma distribution, Gumbel distribution, and Weibull distribution, of which parameters were estimated by the moment method and the maximum likelihood method. The goodness-of-fit test for probability distribution is evaluated by the Kolmogorov-Sminrov test. The fitted distribution function for each duration series is applied to frequency analysis for developing duration-low flow-frequency curves at Yongdam Dam station. It was shown that the purposed technique in this study is available to generate the daily streamflow series with fair accuracy and useful to determine the probabilistic low flow in the watersheds having the poor historic records of low flow series.

• Journal of Korea Water Resources Association
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• v.52 no.4
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• pp.245-253
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• 2019

The objectives of this study are to estimate the return period of flash flood and evaluate its appropriateness based on the actual observation events for small mountainous watersheds in the Han River basin. For these goals, Flash Flood Guidance (FFG) was estimated from 1-hr duration Threshold Runoff (TR) and Saturation Deficit (SD) of soil moisture which was derived from Sejong University Rainfall Runoff (SURR) model. Then, the return period of flash flood was calculated by comparing the rainfall quantile to the 1-hr duration rainfall that exceeded the FFG during the past period (2002-2010). Moreover, the appropriateness of the estimated return period of flash flood was evaluated by using the observation events from 2011 to 2016. The results of the return period of flash flood ranged from 1.1 to 19.9 years with a mean and a standard deviation of 1.6 and 1.1 years, respectively. Also, the result of the appropriateness indicated that 83% of the return periods derived from observation events were within the return period of flash flood range. Therefore, the estimated return period of flash flood could be considered as highly appropriate.

• Journal of Korea Water Resources Association
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• v.35 no.1
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• pp.25-36
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• 2002

Window Probability Matching Method(WPMM) is achieved by matching identical probability density of rain intensities and radar reflectivities taken only from small window centered about the gage. The equation of $Z_{e}-R$ relationship is obtained and compared with data between a DWSR-88C radar and high density rain gage networks within 150km from radar site in summer season, 1998. The probability density of radar effective reflectivity is distributed with high frequency near 15dBZ. The frequency distribution of rain intensities shows that rain intensity is lower than 10mm/hr in most part of radar coverage area. As the result of $Z_{e}-R$ relationship using WPMM, curved line has shown to the log scale spatially and it can be explained more flexible than any straight-line power laws at the transformation to the rainfall amount from $Z_e$ value. During 3 months, total radar cumulative rainfall amount estimated by $Z=200R^{1.6}$ and WPMM relationships are 44 and 80 percentages of total raingage amount, respectively. Therefore, $Z_{e}-R$ relationships by WPMM may be widely needed a statistical method for the computation of accumulated precipitation.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.1132-1136
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• 2004

본 논문은 지금까지의 지점빈도해석의 약점을 보완하기 위하여 지역화의 개념을 사용한 지역빈도해석의 방법에 관한 연구이다. 지점빈도해석은 수문자료의 관측기간이 짧은 경우 정확도에 문제를 발생시킬 수 있으므로, 지점 내 충분한 수의 자료 확보가 선행되어야 한다. 반면 지역빈도해석의 경우 우리나라와 같이 자료의 수가 부족한 경우에도 효율적이고 안정적인 확률수문량을 산정할 수 있다. 본 연구에서는 한강유역의 강우자료 선별을 통해 신뢰성 있는 자료를 구축한 훈, L-모멘트기법과 Netmax법을 사용한 지역빈도해석을 각각 실시하여 기존의 방법으로 산정한 수문량과 비교${\cdot}$분석하였다. 지역빈도해석의 결과 남한강 유역은 이질성 척도가 큰 것으로 판명되어 남한강 유역의 경우 지역적인 세분화가 필요한 것으로 나타났다. Netmax를 이용하여 산정된 수문량은 L-모멘트법과 지점빈도해석 그리고 확률강우량도에 의해 산정된 값에 비하여 과소추정 되었다 지역적 특수성을 고려하지 않고 형성된 네트워크는 지역적으로 세분화가 필요한 지역에 대하여서 좋지 않은 결과를 보여주는 것으로 나타났다.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.256-260
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• 2011

최근 들어 우기시 집중호우로 인한 홍수가 자주 발생하는 편이다. 이러한 현상은 우리나라를 지배하는 일정한 기후양상이 지구 온난화 등의 범지구적인 기후변화 양상에 의하여 변화된 영향으로 판단되고 있는 실정이다. 따라서 기후변화가 미치는 영향은 강우에 직접적으로 나타나며 이는 곧바로 홍수에도 변화가 나타남을 의미한다. 그러므로 "기후변화에 따른 한강유역의 Scaling Invariance와 NSRPM을 이용한 확률강우량 추정"에서 산정된 시나리오별 확률강수량을 적용하여 홍수 유출량을 산정하는 것은 매우 의미가 있을 것으로 판단된다. 본 연구에서는 적용지역으로 우리나라의 대표적인 유역인 한강유역을 선정하였다. 유출량은 HEC-1을 이용하여 산정하였으며, 입력매개변수 중 강수인자는 선행연구에서 NSRPM으로 산정한 확률홍수량을 적용하였으며, 나머지 인자는 한강유역종합치수계획(2008)을 참조하였다. 산정방법으로는 Clark 단위도법을 적용하였으며, NRCS의 CN값을 사용하였다. 2010년을 기준으로 30년 간격으로 이동 구분된 7개의 기후변화 시나리오에 의거하여 홍수유출량을 산정 및 분석하였다. 또한 공간적으로도 도시하여 한강유역의 대표지점에서의 유출량 변화양상 또한 제시하였다. 이러한 산정결과는 향후 기후변화양상을 고려한 수문 설계시 편리하게 활용할 수 있을 것으로 판단된다.