• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.2
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• pp.249-259
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• 2018

More than half of annual rainfall occurs in summer season in Korea due to its climate condition and geographical location. A frequency analysis is mostly adopted for designing hydraulic structure under the such concentrated rainfall condition. Among the various distributions, univariate Gumbel distribution has been routinely used for rainfall frequency analysis in Korea. However, the distributional changes in extreme rainfall have been globally observed including Korea. More specifically, the univariate Gumbel distribution based rainfall frequency analysis is often fail to describe multimodal behaviors which are mainly influenced by distinct climate conditions during the wet season. In this context, we purposed a Gumbel mixture distribution based rainfall frequency analysis with a Bayesian framework, and further the results were compared to that of the univariate. It was found that the proposed model showed better performance in describing underlying distributions, leading to the lower Bayesian information criterion (BIC) values. The mixed Gumbel distribution was more robust for describing the upper tail of the distribution which playes a crucial role in estimating more reliable estimates of design rainfall uncertainty occurred by peak of upper tail than single Gumbel distribution. Therefore, it can be concluded that the mixed Gumbel distribution is more compatible for extreme frequency analysis rainfall data with two or more peaks on its distribution.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.5
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• pp.41-53
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• 2002

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. According to the regions and consecutive durations, optimal design rainfalls were derived by the regional frequency analysis for L-moment in the second report of this project. Using the LH-moment ratios and Kolmogorov-Smirnov test, the optimal regional probability distribution was identified to be the Generalized extreme value (GEV) distribution among applied distributions. regional and at-site parameters of the GEV distribution were estimated by the linear combination of the higher probability weighted moments, LH-moment. Design rainfall using LH-moments following the consecutive duration were derived by the regional and at-site analysis using the observed and simulated data resulted from Monte Carlo techniques. Relative root-mean-square error (RRMSE), relative bias (RBIAS) and relative reduction (RR) in RRMSE for the design rainfall were computed and compared in the regional and at-site frequency analysis. Consequently, it was shown that the regional analysis can substantially more reduce the RRMSE, RBIAS and RR in RRMSE than at-site analysis in the prediction of design rainfall. Relative efficiency (RE) for an optimal order of L-moments was also computed by the methods of L, L1, L2, L3 and L4-moments for GEV distribution. It was found that the method of L-moments is more effective than the others for getting optimal design rainfall according to the regions and consecutive durations in the regional frequency analysis. Diagrams for the design rainfall derived by the regional frequency analysis using L-moments were drawn according to the regions and consecutive durations by GIS techniques.

• Journal of The Geomorphological Association of Korea
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• v.23 no.3
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• pp.105-122
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• 2016

To evaluate the changes in the physical characteristics of open rainfall related to canopy effects and rainfall intensity in Korea, the terminal velocity of raindrops and drop size distributions(DSD) were continuously measured by an optical-laser disdrometer in an open site(Op) and in two forest stands(Th1: Larix leptolepis, Th2: Pinus koraiensis) during five rainfall events in 2008. The terminal velocity, DSD and two forms of kinetic energy(KE, $Jm^{-2}$ $mm^{-1}$; KER, $Jm^{-2}$ $h^{-1}$) of open rainfall drops were determined and were compared with those of throughfall drops under two different canopy heights. The effects of the canopy and rainfall intensity, together with wind speed, on the changes in drop size and kinetic energy of throughfall were evaluated. Throughfall drops were larger than open rainfall drops. The distribution of terminal velocities for the drop sizes measured at Th2 was lower than that at Op; however, at Th1 the distribution was similar to that at Op. The total kinetic energy of throughfall at Th1 and Th2 was higher than the total kinetic energy of open rainfall, and the kinetic energy distribution for the drop sizes wassimilar to the drop size distribution. The observed throughfall-KER at Th1 was lower than an estimate previously produced using a model. The overestimation from the modeled value at Th1 was likely to be due to overestimated values of a square root transformation of fall height and its coefficient in the model because the distributions of terminal velocity for the drop size measured at Th1 were similar to those of open rainfall.

• 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.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.110-113
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• 2016

In this paper of ka band satellite communication using geostationary satellite is very weak to rainfall. So the rain attenuation reflect the values calculated using the satellite communication links vulnerable when designing a more reliable rainfall area distribution of rain attenuation and accurate predictive models must analyze the link budget. In this paper, by utilizing domestic distribution analysis in the recent local rainfall Crane and regional rainfall in the model and compared with the country of the regional distribution of rainfall in your area to fit the rain attenuation in Ka band frequency characteristics Crane rain attenuation prediction models were analyzed to between geostationary satellites and ground station position, distance and year time percentage(%).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4B
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• pp.315-322
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• 2011

This study reviewed the Weiss model, probably the only theoretical study available on the fixed- to true-interval rainfall conversion factor (CF), and implemented to propose a modified Weiss model. Also, the characteristics of the temporal distribution of rainfall were considered in the estimation of CF to overcome the problem of these two models, whose results were compared with those estimated empirically. As results, the CF was found to be differently estimated depending on the temporal distribution of rainfall. Especially, the theoretical CF estimate for the center-concentrated rainfall distribution was found to be very similar to that of empirical results of domestic and foreign studies.

• Journal of Korea Water Resources Association
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• v.31 no.4
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• pp.375-384
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• 1998

In determining design runoff for the design of drainage systems, the concept of critical storm duration is applied. However, rainfall distribution is usually determined without well-defined standards. In this paper, through the application of ILLUDAS model to Sanbon basin, which is a small urbanized watershed, effects of various rainfall distributing types upon the determination of critical storm duration are throughly analyzed. As a result, it is revealed that peak discharge rates as well as critical storm duration are greatly influenced by the applied of rainfall distributions such as uniform, triangular, trapezoid, huff, central type using IDF curve. Keywords : critical storm duration, rainfall distribution, urban runoff, design storm, ILLUDAS.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.757-767
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• 2010

This study employs the KED method using the correlations between probability rainfall and topographical factors as single auxiliary variable for assessing the effectiveness of external variables to improve the reliability in the estimation of spatial distribution of probability rainfall. As a result, the KED method gives similar results compared with deterministic spatial interpolation methods and kriging methods in the estimation of rainfall spatial distribution and mean areal rainfall, and as a result of the cross-validations of KED and kriging methods, the KED method using terrain elevation as auxiliary variable gives the best results, which are not significantly different in comparisons with other methods.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1069-1076
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• 2014

Rainfall weather patterns have changed due to global warming and sudden heavy rainfalls have become more frequent. Economic loss due to heavy rainfall has increased. We study the generalized Pareto distribution for modelling rainfall in Seoul based on data from 1973 to 2008. We use several priors including Jeffrey's noninformative prior and Gibbs sampling method to derive Bayesian posterior predictive distributions. The probability of heavy rainfall has increased over the last ten years based on estimated posterior predictive distribution.

• Journal of Korea Water Resources Association
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• v.52 no.11
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• pp.895-904
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• 2019

It has been well recognized that extreme rainfall process often features a nonstationary behavior, which may not be effectively modeled within a stationary frequency modeling framework. Moreover, extreme rainfall events are often described by a two (or more)-component mixture distribution which can be attributed to the distinct rainfall patterns associated with summer monsoons and tropical cyclones. In this perspective, this study explores a Mixture Distribution based Nonstationary Frequency (MDNF) model in a changing rainfall patterns within a Bayesian framework. Subsequently, the MDNF model can effectively account for the time-varying moments (e.g. location parameter) of the Gumbel distribution in a two (or more)-component mixture distribution. The performance of the MDNF model was evaluated by various statistical measures, compared with frequency model based on both stationary and nonstationary mixture distributions. A comparison of the results highlighted that the MDNF model substantially improved the overall performance, confirming the assumption that the extreme rainfall patterns might have a distinct nonstationarity.