• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.431-444
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• 2012

This study investigated the differences between annual maximum series and annual maximum independent rainfall event series with relatively short and long rainfall durations. Annual maximum independent rainfall events were selected by applying various IETDs and thresholds to the hourly rainfall data in Seoul for the duration from 1961 to 2010. Annual maximum independent rainfall event series decided were then compared with the conventional annual maximum series. Summarizing the results is as follows. First, the effect of IETD and threshold was not beyond the expected level. For example, as the IETD increases, the frequencies of independent rainfall events decreased similarly in their rate for both with short and long durations. However, as the threshold increases, the frequency of those with rather long durations decreased much higher. Second, The mean rainfall intensity of the independent rainfall events was found to remain constant regardless of their duration. This indicates that the annual maximum rainfall intensity could be found in a rainfall event with longer durations. Lastly, the difference between the annual maximum rainfall series and the annual maximum independent rainfall event series with rather short rainfall durations was found significantly large, which decreases with longer durations. This result indicates that the conventional data analysis method, especially for small basins with short concentration time, could lead an unrealistic design rainfall with little possibility of occurrence.

• Journal of Korea Water Resources Association
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• v.46 no.4
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• pp.361-372
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• 2013

This study used the beta distribution to analyze the independent annual maximum rainfall events from 1961 to 2010 and decided the representative rainfall event for Seoul. In detail, the annual maximum rainfall events were divided into two groups, the upper 50% and the lower 50%. For each group, a beta distribution was derived to pass the mean location of the rainfall peaks. Finally, the representative rainfall event was decided as the rainfall histogram of the arithmetic average of the two beta distributions derived. The representative rainfall event derived has a realistic shape very similar to those observed annual maximum rainfall events, especially with the higher rainfall peak compared to that of the Huff distribution. Comparison with other rainfall distribution models shows that the temporal distribution of the representative rainfall event derived in this study is most similar to the Keifer & Chu model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.137-147
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• 2010

In this study, Chukwooki and modern data were compared using annual maximum rainfall event series. Annual maximum series for specified rainfall duration in modern frequency analysis can not be constructed from Chukwooki data, so the concept of independent rainfall event is introduced to compare Chukwooki and modern data. Annual maximum rainfall event is determined by applying the bivariate exponential distribution and the parameters estimated annually are selected. The results using the annual parameter show that the hydrological meaning of the parameters is related to the variation of annual total rainfall amounts. For the whole independent rainfall events, the total rainfall and the rainfall intensity of Chukwooki data are greater than those of modern data, and rainfall duration of the two periods is similar. However modern annual maximum rainfall events show different characteristics that rainfall duration is much longer, rainfall intensity is similar and the total rainfall is greater than those of Chukwooki period. The increasing trend of rainfall duration and total rainfall of the modern annual rainfall events may be regarded as the one of components of the long-term cycle.

• Journal of Korea Water Resources Association
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• v.45 no.2
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• pp.191-201
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• 2012

This study reviewed the parameter estimation procedure of the Freund bivariate exponential distribution for the decision of the annual maximum rainfall event. The method of moments was reviewed first, whose results were compared with those from the method of maximum likelihood. Both methods were applied to the hourly rainfall data of the Seoul rain gauge station measured from 1961 to 2010 to select the annual maximum rainfall events, which were also compared each other. The results derived are as follows. First, when applying the method of moments for the parameter estimation, it was found necessary to consider the correlation coefficient between the two variables as well as the mean and variance. Second, the method of maximum likelihood was better to reproduce the mean, but the method of moments was better to reproduce the annual variation of the variance. Third, The annual maximum rainfall events derived were very similar in both cases. Among differently selected annual maximum rainfall events, those with the higher rainfall amount were selected by the method of maximum likelihood, but those with the higher rainfall intensity by the method of moments.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.260-260
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• 2016

Soil erosion is a very serious problem from agricultural as well as environmental point of view. Various computer models have been used to estimate soil erosion and assess erosion control practice. Universal Soil loss equation (USLE) is a popular model which has been used in many countries around the world. Erosivity (USLE R-factor) is one of the USLE input parameters to reflect impacts of rainfall in computing soil loss. Value of R factor depends upon Energy (E) and maximum rainfall intensity of specific period ($I30_{max}$) of that rainfall event and thus can be calculated using higher temporal resolution rainfall data such as 10 minute interval. But 10 minute interval rainfall data may not be available in every part of the world. In that case we can use hourly rainfall data to compute this R factor. Maximum 60 minute rainfall ($I60_{max}$) can be used instead of maximum 30 minute rainfall ($I30_{max}$) as suggested by USLE manual. But the value of Average annual R factor computed using hourly rainfall data needs some correction factor so that it can be used in USLE model. The objective of our study are to derive relation between averages annual R factor values using 10 minute interval and hourly rainfall data and to determine correction coefficient for R factor using hourly Rainfall data.75 weather stations of Korea were selected for our study. Ten minute interval rainfall data for these stations were obtained from Korea Meteorological Administration (KMA) and these data were changed to hourly rainfall data. R factor and $I60_{max}$ obtained from hourly rainfall data were compared with R factor and $I30_{max}$ obtained from 10 minute interval data. Linear relation between Average annual R factor obtained from 10 minute interval rainfall and from hourly data was derived with $R^2=0.69$. Correction coefficient was developed for the R factor calculated using hourly rainfall data.. Similarly, the relation was obtained between event wise $I30_{max}$ and $I60_{max}$ with higher $R^2$ value of 0.91. Thus $I30_{max}$ can be estimated from I60max with higher accuracy and thus the hourly rainfall data can be used to determine R factor more precisely by multiplying Energy of each rainfall event with this corrected $I60_{max}$.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.2
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• pp.127-136
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• 2011

In this study, annual maximum storm events are proposed to determined by the return periods considering total rainfall and rainfall intensity together. The rainfall series at Seoul since 1961 are examined and the results are as follows. First, the bivariate exponential distribution is used to determine annual maximum storm events. The parameter estimated annually provides more suitable results than the parameter estimated by whole periods. The chosen annual maximum storm events show these properties. The events with the biggest total rainfall tend to be selected in the wet years and the events with the biggest rainfall intensity in the wet years. These results satisfy the concept of critical storm events which produces the most severe runoff according to soil wetness. The average characteristics of the annual maximum storm events said average rainfall intensity 32.7 mm/hr in 1 hr storm duration(total rainfall 32.7 mm), average rainfall intensity 9.7 mm/hr in 24 hr storm duration(total rainfall 231.6 mm) and average rainfall intensity 7.4 mm/hr in 48 hr storm duration(total rainfall 355.0 mm).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.469-478
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• 2014

The annual maximum series (AMS) is usually used to estimate hydrological quantiles in practice because it is simple to construct and straightforward to probabilistic interpretation. However, it is limited to use the AMS in Korea due to the lack of reliable observed data which leads to the overestimation of design rainfall and/or flood. Using the 40-year observations of rainfall provided by the Korea Meteorological Administration, this study constructed the AMS and non-annual exceedance series (NAES) after identifying the independent storm event, analyzed the correlation between design rainfalls estimated from the AMS and NAES, and proposed a new method of point frequency analysis to estimate design rainfalls from the small number of observations.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.857-866
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• 2009

In this study, basic data is consisted annual maximum rainfall at 56 stations that has the rainfall records more than 30years in Korea. The 14 probability distributions which has been widely used in hydrologic frequency analysis are applied to the basic data. The method of moments, method of maximum likelihood and probability weighted moments method are used to estimate the parameters. And 4-tests (chi-square test, Kolmogorov-Smirnov test, Cramer von Mises test, probability plot correlation coefficient (PPCC) test) are used to determine the goodness of fit of probability distributions. This study emphasizes the necessity for considering the variability of the estimate of T-year event in hydrologic frequency analysis and proposes a framework for evaluating probability distribution models. The variability (or estimation error) of T-year event is used as a criterion for model evaluation as well as three goodness of fit criteria (SLSC, MLL, and AIC) in the framework. The Jackknife method plays a important role in estimating the variability. For the annual maxima of rainfall at 56 stations, the Gumble distribution is regarded as the best one among probability distribution models with two or three parameters.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.2
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• pp.137-146
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• 2011

In this study, annual maximum storm events are evaluated by applying the bivariate extremal distribution. Rainfall quantiles of probabilistic storm event are calculated using OR case joint return period, AND case joint return period and interval conditional joint return period. The difference between each of three joint return periods was explained by the quadrant which shows probability calculation concept in the bivariate frequency analysis. Rainfall quantiles under AND case joint return periods are similar to rainfall depths in the univariate frequency analysis. The probabilistic storm events overcome the primary limitation of conventional univariate frequency analysis. The application of these storm event analysis provides a simple, statistically efficient means of characterizing frequency of extreme storm event.

• Journal of the Korea Organic Resources Recycling Association
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• v.24 no.2
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• pp.31-39
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• 2016

Due to the temporal variation of inflow/outflow, the water tank is needed. For the calculation of water tank capacity, the absolute difference between cumulative amounts of supply(e.g., rainfall) and demand(e.g.,watering) is used. No matter the (-) and (+) the absolute maximum capacity of the subtraction is calculated as the capacity. In this paper, using rainfall and watering of greenhouse facilities, it is proved that the non-linear supply or demand can be applied, and it is proved also that the greater non-linear variation case. And as the time interval for monitoring is decreased, the basin or tank volume are increased, with approximately 10 days as the critical monitoring interval for the annual natural rainfall event.