• Title/Summary/Keyword: 확률강우량의 추정

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Uncertainty Analysis of Spatial Distribution of Probability Rainfall: Comparison of CEM and SGS Methods (확률강우량의 공간분포에 대한 불확실성 해석: CEM과 SGS 기법의 비교)

  • Seo, Young-Min;Yeo, Woon-Ki;Lee, Seung-Yoon;Jee, Hong-Kee
    • Journal of Korea Water Resources Association
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    • v.43 no.11
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    • pp.933-944
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    • 2010
  • This study compares the CEM and SGS methods which are geostatistical stochastic simulation methods for assessing the uncertainty by spatial variability in the estimation of the spatial distribution of probability rainfall. In the stochastic simulations using CEM and SGS, two methods show almost similar results for the reproduction of spatial correlation structure, the statistics (standard deviation, coefficient of variation, interquartile range, and range) of realizations as uncertainty measures, and the uncertainty distribution of basin mean rainfall. However, the CEM is superior to SGS in aspect of simulation efficiency.

Analysis Method for Spatial Distribution of Design Storms (설계호우의 공간분포 분석 방법)

  • Kim, Nam Won;Won, Yoo Seung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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    • pp.604-609
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    • 2004
  • 일반적으로 설계호우(확률강우량, PMP 등)는 유역중심에서의 추정되고, 이 값을 유역의 평균강우량으로 이용한다. 그러나, 실제호우는 유역의 형상에 대해 지속기간 동안 균일하게 발생하지 않으려, 이러한 현상을 분석에 적절히 고려하기 위해서 호우의 공간분포에 대한 분석이 필요하다. 또한 유역면적이 크고, 소유역으로 분할된 중${\cdot}$대규모 유역조차도 균일한 설계호우 값을 적용함으로써 평균강우량 및 출력 값을 과대하게 산정할 수 있다. 따라서 본 연구에서는 설계호우의 공간분포를 기왕의 실제호우로부터 가상호우의 형태를 가정하였으며, 이 가상호우의 형태에 따라 설계호우를 대상유역에 공간분포시켜 평균강우량을 재산정하는 절차를 예를 들어 상세히 기술하였다.

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Development of spatial dependence formula of FORGEX method using rainfall data in Korea (우리나라 강우 자료를 이용한 FORGEX 기법의 공간상관식 개발)

  • Kim, Sunghun;Ahn, Hyunjun;Shin, Hongjoon;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.49 no.12
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    • pp.1007-1014
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    • 2016
  • The FORGEX (Focused Rainfall Growth Extension) method was developed to estimate rainfall quantiles in the United Kingdom. This method does not need any regional grouping and can estimate rainfall quantiles with relatively long return period. The spatial dependence formula (ln $N_e$) was derived to consider the distance from growth curve of proper population to the distributed network maximum (netmax) data using the UK rainfall data. For this reason, there is an inaccurate problem in rainfall quantiles when this formula is applied in Korea. In this study, the new formula was derived in order to improve such shortcomings using rainfall data of 64 sites from the Korea Meteorological Administration (KMA). A 42-year period (1973~2014) was taken as the reference period from rainfall data, then the formula was derived using three parameters such as rainfall duration, number of site, area of network. Then the new formula was applied to the FORGEX method for regional rainfall frequency analysis. In addition, rainfall quantiles were compared with those from the UK formula. As a result, the new formula shows more accurate results than the UK formula, in which the FORGEX method by the UK formula underestimates rainfall quantiles. Finally, the new improved formula may estimate accurate rainfall quantiles for long return period.

Estimating Quantiles of Extreme Rainfall Using a Mixed Gumbel Distribution Model (혼합 검벨분포모형을 이용한 확률강우량의 산정)

  • Yoon, Phil-Yong;Kim, Tae-Woong;Yang, Jeong-Seok;Lee, Seung-Oh
    • Journal of Korea Water Resources Association
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    • v.45 no.3
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    • pp.263-274
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    • 2012
  • Recently, due to various climate variabilities, extreme rainfall events have been occurring all over the world. Extreme rainfall events in Korea mainly result from the summer typhoon storms and the localized convective storms. In order to estimate appropriate quantiles for extreme rainfall, this study considered the probability behavior of daily rainfall from the typhoons and the convective storms which compose the annual maximum rainfalls (AMRs). The conventional rainfall frequency analysis estimates rainfall quantiles based on the assumption that the AMRs are extracted from an identified single population, whereas this study employed a mixed distribution function to incorporate the different statistical characteristics of two types of rainfalls into the hydrologic frequency analysis. Selecting 15 rainfall gauge stations where contain comparatively large number of measurements of daily rainfall, for various return periods, quantiles of daily rainfalls were estimated and analyzed in this study. The results indicate that the mixed Gumbel distribution locally results in significant gains and losses in quantiles. This would provide useful information in designing flood protection systems.

Non-stationary Rainfall Frequency Analysis Based on Residual Analysis (잔차시계열 분석을 통한 비정상성 강우빈도해석)

  • Jang, Sun-Woo;Seo, Lynn;Kim, Tae-Woong;Ahn, Jae-Hyun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.31 no.5B
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    • pp.449-457
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    • 2011
  • Recently, increasing heavy rainfalls due to climate change and/or variability result in hydro-climatic disasters being accelerated. To cope with the extreme rainfall events in the future, hydrologic frequency analysis is usually used to estimate design rainfalls in a design target year. The rainfall data series applied to the hydrologic frequency analysis is assumed to be stationary. However, recent observations indicate that the data series might not preserve the statistical properties of rainfall in the future. This study incorporated the residual analysis and the hydrologic frequency analysis to estimate design rainfalls in a design target year considering the non-stationarity of rainfall. The residual time series were generated using a linear regression line constructed from the observations. After finding the proper probability density function for the residuals, considering the increasing or decreasing trend, rainfalls quantiles were estimated corresponding to specific design return periods in a design target year. The results from applying the method to 14 gauging stations indicate that the proposed method provides appropriate design rainfalls and reduces the prediction errors compared with the conventional rainfall frequency analysis which assumes that the rainfall data are stationary.

A Study of the high return period flood quantiles Estimation using upper bounded statistical models (상한분포함수를 활용한 고빈도 홍수빈도해석에 관한 연구)

  • Kim, Jang-Gyeong;Park, Rae-Kon;Kim, Kyung-Wook;Kwon, Hyun-Han
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.402-402
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    • 2017
  • 수공구조물 설계 시, 설계홍수량 산정에는 실측 홍수량 자료를 활용한 홍수빈도해석이 필요하다. 그러나 홍수량 자료의 관측연한, 유역변화 등의 신뢰성 문제로 확률강우량을 활용한 빈도홍수량 간접추정방법이 표준화된 실정이다. 문제는 확률강우량 산정에 활용된 확률밀도함수와 그 매개변수에 따른 불확실성이 존재한다는 점이다. 특히 저빈도에서 고빈도로 갈수록 확률밀도함수의 불확실성은 크게 증가하여, 사실상 추정결과에 대한 물리적 의미를 부여하기 어렵다. 이에 본 연구에서는 PMF를 물리적 상한선으로 설정하는 상한분포함수(Upper bounded distribution functions)를 적용하여, 실측 홍수량에 대한 홍수빈도해석 방법을 제안하고자 한다. 검정방법은 먼저, 임의 유역을 대상유역으로 선정하여 홍수빈도해석을 수행하고, 상한분포함수는 EV4, LN4, TDF를 적용한다. 최종적으로 빈도홍수량 간접추정방법과 비교 분석하여, 적용성을 검토하고자 한다. 본 연구결과는 빈도홍수량 간접추정방법에 대한 비교 검토방법에 대한 적절한 대안이 없다는 측면에서 의의를 찾을 수 있으며, 향후 홍수량 자료 신뢰성이 확보되는 시점에서 지역홍수빈도 분석으로 확장할 수 있을 것으로 판단된다.

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Bivariate Frequency Analysis of Rainfall using Copula Model (Copula 모형을 이용한 이변량 강우빈도해석)

  • Joo, Kyung-Won;Shin, Ju-Young;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.45 no.8
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    • pp.827-837
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    • 2012
  • The estimation of the rainfall quantile is of great importance in designing hydrologic structures. Conventionally, the rainfall quantile is estimated by univariate frequency analysis with an appropriate probability distribution. There is a limitation in which duration of rainfall is restrictive. To overcome this limitation, bivariate frequency analysis by using 3 copula models is performed in this study. Annual maximum rainfall events in 5 stations are used for frequency analysis and rainfall depth and duration are used as random variables. Gumbel (GUM), generalized logistic (GLO) distributions are applied for rainfall depth and generalized extreme value (GEV), GUM, GLO distributions are applied for rainfall duration. Copula models used in this study are Frank, Joe, and Gumbel-Hougaard models. Maximum pseudo-likelihood estimation method is used to estimate the parameter of copula, and the method of probability weighted moments is used to estimate the parameters of marginal distributions. Rainfall quantile from this procedure is compared with various marginal distributions and copula models. As a result, in change of marginal distribution, distribution of duration does not significantly affect on rainfall quantile. There are slight differences depending on the distribution of rainfall depth. In the case which the marginal distribution of rainfall depth is GUM, there is more significantly increasing along the return period than GLO. Comparing with rainfall quantiles from each copula model, Joe and Gumbel-Hougaard models show similar trend while Frank model shows rapidly increasing trend with increment of return period.

Parameter Estimation of Intensity-Duration-Frequency Curve using Genetic Algorithm (유전자 알고리즘을 이용한 강우강도식의 매개변수 추정에 관한 연구)

  • Shin, Ju-Young;Kim, Soo-Young;Kim, Tae-Soon;Heo, Jun-Haeng
    • Proceedings of the Korea Water Resources Association Conference
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    • 2007.05a
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    • pp.142-146
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    • 2007
  • 본 연구에서는 강우강도식의 매개변수를 보다 효율적으로 산정하기 위해서 유전자알고리즘을 적용한 매개변수 산정법을 제시하였으며, 지속기간의 장, 단기간에 따른 매개변수의 변화를 고려하기 위하여 다목적 유전자알고리즘을 적용하여 매개변수를 추정한 후 기존의 강우강도식에 의한 결과와 비교해 보았다. 매개변수는 지점빈도해석을 통해 산정된 확률강우량을 사용하여 추정하였고, 유전자 알고리즘의 목적함수로는 Nash & Sutcliffe Index, Root Mean Square Error(RMSE), Relative Root Mean Square Error(RRMSE), 결정계수, 평균들을 사용하여 가장 효율적인 형태의 목적함수를 구성하였다. 그 결과 기존의 매개변수 추정 방법들에 비해 유전자알고리즘을 이용한 경우에 더 정확한 강우량값을 산정할 수 있었고, 특히 다목적 유전자 알고리즘을 사용할 경우 장기간과 단기간에 걸쳐서 동시에 정확도를 향상시킬 수 있는 매개변수를 추정할 수 있는 것으로 나타났다.

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Concept of Trend Analysis of Hydrologic Extreme Variables and Nonstationary Frequency Analysis (극치수문자료의 경향성 분석 개념 및 비정상성 빈도해석)

  • Lee, Jeong-Ju;Kwon, Hyun-Han;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.4B
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    • pp.389-397
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    • 2010
  • This study introduced a Bayesian based frequency analysis in which the statistical trend analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both Gumbel distribution and trend analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions.

Evaluation of Extreme Rainfall based on Typhoon using Nonparametric Monte Carlo Simulation and Locally Weighted Polynomial Regression (비매개변수적 모의발생기법과 지역가중다항식을 이용한 태풍의 극치강우량 평가)

  • Oh, Tae-Suk;Moon, Young-Il;Chun, Si-Young;Kwon, Hyun-Han
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.2B
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    • pp.193-205
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    • 2009
  • Typhoons occurred in the tropical Pacific region, these might be affected the Korea moving toward north. The strong winds and the heavy rains by the typhoons caused a natural disaster in Korea. In the research, the heavy rainfall events based on typhoons were evaluated quantitative through various statistical techniques. First, probability precipitation and typhoon probability precipitation were compared using frequency analysis. Second, EST probability precipitation was calculated by Empirical Simulation Techniques (EST). Third, NL probability precipitation was estimated by coupled Nonparametric monte carlo simulation and Locally weighted polynomial regression. At the analysis results, the typhoons can be effected Gangneung and Mokpo stations more than other stations. Conversely, the typhoons can be effected Seoul and Inchen stations less than other stations. Also, EST and NL probability precipitation were estimated by the long-term simulation using observed data. Consequently, major hydrologic structures and regions where received the big typhoons impact should be review necessary. Also, EST and NL techniques can be used for climate change by the global warming. Because, these techniques used the relationship between the heavy rainfall events and the typhoons characteristics.