• Wind and Structures
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• v.1 no.2
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• pp.145-160
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• 1998

In recent years, the effects of a possible climate change have been discussed in regard to wind loading on buildings and structures. Simple scenarios based on the assumption of global warming suggest an increase of storm intensities and storm frequencies and a possible re-distribution of storm tracks. Among recent publications, some papers seem to verify these scenarios while others deny the influence of climatic change. In an introductory step, the paper tries to re-examine these statements. Based on meteorological observations of a weather station in Germany, the existence of long-term trends and their statistical significance is investigated. The analysis itself is based on a refined model for the wind climate introducing a number of new basic variables. Thus, the numerical values of the design wind loads used in modern codes become more justified from the probabilistic point of view.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.733-745
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• 2010

Seasonality of hydrologic extreme variable is a significant element from a water resources managemental point of view. It is closely related with various fields such as dam operation, flood control, irrigation water management, and so on. Hydrological frequency analysis conjunction with partial duration series rather than block maxima, offers benefits that include data expansion, analysis of seasonality and occurrence. In this study, nonstationary frequency analysis based on the Bayesian model has been suggested which effectively linked with advantage of POT (peaks over threshold) analysis that contains seasonality information. A selected threshold that the value of upper 98% among the 24 hours duration rainfall was applied to extract POT series at Seoul station, and goodness-fit-test of selected GEV distribution has been examined through graphical representation. Seasonal variation of location and scale parameter ($\mu$ and $\sigma$) of GEV distribution were represented by Fourier series, and the posterior distributions were estimated by Bayesian Markov Chain Monte Carlo simulation. The design rainfall estimated by GEV quantile function and derived posterior distribution for the Fourier coefficients, were illustrated with a wide range of return periods. The nonstationary frequency analysis considering seasonality can reasonably reproduce underlying extreme distribution and simultaneously provide a full annual cycle of the design rainfall as well.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1421-1433
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• 2014

In this study, appropriate probability distribution and parameter estimation method were selected to perform snowfall frequency analysis. Generalized Extreme Value (GEV) and Probability Weighted Moment Method (PWMM) appeared to be the best fit for snowfall frequency analysis in Korea. Snowfall frequency analysis applying GEV and PWMM were performed for 69 stations in Korea. Peak snowfall corresponding to recurrence intervals were estimated based on frequency analysis while snow loads were calculated using the estimated peak snowfall and specific weight of snow. Design snow load map was developed using 100-year recurrence interval snow load of 69 stations through Kriging of ArcGIS. The 2009 Korean Building Code and Commentary for design snow load was assessed by comparing the design snow loads which calculated in this study. As reflected in the results, most regions are required to increase the design snow loads. Thus, design snow loads and the map were developed from based on the results. The developed design snow load map is expected to be useful in the design of building structures against heavy snow loading throughout Korea most especially in ungaged areas.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.5
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• pp.343-351
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• 2012

In this study, shallow-water design waves are calculated for the return period of 10, 20, 30, and 50 years, based on the extreme value analysis of the wave measurement data at Gangneung beach. These values are compared with the results of SWAN simulation with the boundary condition of the deep-water design waves of the corresponding return periods at the Gangneung sea area provided by the Fisheries Agency (FA, 1988) and Korea Ocean Research & Development Institute (KORDI, 2005). It is found that the shallow-water wave heights at Gangneung beach calculated by the deep-water design waves were significantly less than the observation data. As the return period becomes higher, the significant wave heights obtained by the extreme value analysis becomes higher than those computed by SWAN with the deep-water design waves of the corresponding return periods. KORDI computed the hindcast wave data from January 2004 to August 2008 by WAM with a finer-grid mesh system than those of previous studies. Comparisons of the wave hindcast results with the wave observation show that the reproducibility of the winter-season storm wave was considerably improved compared to the hindcast data from 1979 to 2003. Hereafter, it is necessary to carry out hindcast wave data for the years before 2004 using WAM with the finer-grid mesh system and to supplement the deep-water design wave.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.139-152
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• 2015

Along with climate change, it is reported that the scale and frequency of extreme climate events show unstable tendency of increase. Thus, to comprehend the change characteristics of precipitation data, it is needed to consider non-stationary. The main objectives of this study were to estimate future design floods for Wonpyeongcheon watershed based on RCP (Representative Concentration Pathways) scenario. Wonpyeongcheon located in the Keum River watershed was selected as the study area. Historical precipitation data of the past 35 years (1976~2010) were collected from the Jeonju meteorological station. Future precipitation data based on RCP4.5 were also obtained for the period of 2011~2100. Systematic bias between observed and simulated data were corrected using the quantile mapping (QM) method. The parameters for the bias-correction were estimated by non-parametric method. A non-stationary frequency analysis was conducted with moving average method which derives change characteristics of generalized extreme value (GEV) distribution parameters. Design floods for different durations and frequencies were estimated using rational formula. As the result, the GEV parameters (location and scale) showed an upward tendency indicating the increase of quantity and fluctuation of an extreme precipitation in the future. The probable rainfall and design flood based on non-stationarity showed higher values than those of stationarity assumption by 1.2%~54.9% and 3.6%~54.9%, respectively, thus empathizing the necessity of non-stationary frequency analysis. The study findings are expected to be used as a basis to analyze the impacts of climate change and to reconsider the future design criteria of Wonpyeongcheon watershed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.227-234
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• 2004

Recently huge typhoons had attacked to the coastal waters in Korea and caused disastrous casualties in those area. There are some discussions on correction to the design parameters for the coastal structures. Wave transformation computations with the extreme waves are of value in planning and constructing engineering works, especially in coastal regions. Prediction of typhoon surge elevations is based primarily on the use of a numerical model in this study, since it is difficult to study these events in real time or with use of physical models. Wave prediction with a two dimensional numerical model for a site with complicated coastal lines and structures at the period of typhoon 'Maemi' is discussed. In order to input parameters for the extreme wave conditions, we analyzed the observed and predicted typhoon data. Finally we applied the model discussed above to the storm surge and extreme wave problem at Busan Harbor, the southeast coast of Korea. Effects of water level variation and transformation of the extreme waves in relation with the flooding in coastal waters interested are analyzed. We then mack an attempt to presen a basic hazard map for the corresponding site.

• Journal of the Korean Society of Safety
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• v.31 no.4
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• pp.48-54
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• 2016

The prediction of various emissions from coal combustion is an important subject of researchers and engineers because of environmental consideration. Therefore, the development of the models for predicting pollutants very fast has received much attention from international research community, especially in the field of safety assessment. In this work, response surface method was introduced as a design of experiment, and the database for RSM was set with the numerical simulation of a drop tube furnace (DTF) to predict the spatial distribution of pollutant concentrations as well as final ones. The distribution of carbon dioxide in DTF was assumed to have Boltzman function, and the resulted function with parameters of a high $R^2$ value facilitates predicting an accurate distribution of $CO_2$. However, CO distribution had a difference near peak concentration when Gaussian function was introduced to simulate the CO distribution. It might be mainly due to the anti-symmetry of the CO concentration in DTF, and hence Extreme function was used to permit the asymmetry. The application of Extreme function enhanced the regression accuracy of parameters and the prediction was in a fairly good agreement with the new experiments. These results promise the wide use of statistical models for the quantitative safety assessment.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.15-26
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• 2004

This study was conducted to derive the regional design rainfall by the regional frequency analysis based on the regionalization of the precipitation. The optimal regionalization of the precipitation data were classified by the above mentioned regionalization for all over the regions except Jeju and Ulleung islands in Korea. Design rainfalls following the consecutive duration were derived by the regional 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 between the regional and at-site frequency analysis. It has shown that the regional frequency analysis procedure can substantially more reduce the RRMSE, RBIAS and RR in RRMSE than those of at-site analysis in the prediction of design rainfall. Consequently, optimal design rainfalls following the classified regions and consecutive durations were derived by the regional frequency analysis using Generalized extreme value distribution which was identified to be more optimal one than the other applied distributions. 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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.41 no.3
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• pp.41-50
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• 1999

Derivatio of reasonable design floods was attempted by comparative analysis of design floods derived by Generalized Extreme Value(GEV) distribution using methods of L-moments and LH-moments for the annual maximum series at ten watersheds along Han, Nagdong. Geum, Yeongsan and Seomjin river systems, LH-coefficient of variation, LH-skewness and Lh-kurtosis were calcualted by KH-moment ration respectively. Paramenters were estimated by the Method of LH-Moments, Design floods obtained by Method of LH-Moments using different methods for plotting positionsi n GEV distribution and design floods were compared with those obtained using the Method of L-Moments by the Relative Mean Errors(RME) and Relative Absolute Errors(RAE). The results was found that design floods derived by the method of L-Moments and LH-Moments using Cunnane plotting position formula in the GEV distribution are much closer to those of the observed data in comparison with those obtained by methods of L-moments and LH-moments using the other formula for plotting positions from the viewpoint of Relative Mean Errors and Relative Absolute Errors. In viewpoint of the fact that hydrqulic structures including dams and levees are genrally using design floods with the return period of two hundred years or so, design floods derived by LH-Moments are seemed to be more reasonable than those of L-Moments in the GEV distribution.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.16-16
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• 2011

Statistics of extreme rainfall play a vital role in engineering practice from the perspective of mitigation and protection of infrastructure and human life from flooding. While flood frequency assessments, based on river flood flow data are preferred, the analysis of rainfall data is often more convenient due to the finer spatial nature of rainfall recording networks, often with longer records, and potentially more easily transferable from site to site. The rainfall frequency analysis as a design tool has developed over the years in New Zealand from Seelye's daily rainfall frequency maps in 1947 to Thompson's web based tool in 2010. This paper will present a history of the development of New Zealand rainfall frequency analysis methods, and the details of the latest method, so that comparisons may in future be made with the development of Korean methods. One of the main findings in the development of methods was new knowledge on the distribution of New Zealand rainfall extremes. The High Intensity Rainfall Design System (HIRDS.V3) method (Thompson, 2011) is based upon a regional rainfall frequency analysis with the following assumptions: $\bullet$ An "index flood" rainfall regional frequency method, using the median annual maximum rainfall as the indexing variable. $\bullet$ A regional dimensionless growth curve based on the Generalised Extreme Value (GEV), and using goodness of fit test for the GEV, Gumbel (EV1), and Generalised Logistic (GLO) distributions. $\bullet$ Mapping of median annual maximum rainfall and parameters of the regional growth curves, using thin-plate smoothing splines, a $2km\times2km$ grid, L moments statistics, 10 durations from 10 minutes to 72 hours, and a maximum Average Recurrence Interval of 100 years.