• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.2
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• pp.108-122
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• 1996

This study was to introduced estimation model for optimum probabilistic rainfall intensity on hydrological area. Originally, probabilistic rainfall intensity formula have been characterized different coefficient of formula and model following watersheds. But recently in korea rainfall intensity formula does not use unionize applyment standard between administration and district. And mingle use planning formula with not assumption model. Following the number of year hydrological duration adjust areal index. But, with adjusting formula applyment was without systematic conduct. This study perceive the point as following : 1) Use method of excess probability of Iwai to calculate survey rainfall intensity value. 2) And, use method of least squares to calculate areal coefficient for a unit of 157 rain gauge station. And, use areal coefficient was introduced new probabilistic rainfall intensity formula for each rain gauge station. 3) And, use new probabilistic rainfall intensity formula to adjust a unit of fourteen duration-a unit of fifteen year probabilistic rainfall intensity. 4) The above survey value compared with adjustment value. And use three theory of error(absolute mean error, squares mean error, relative error ratio) to choice optimum probabilistic rainfall intensity formula for a unit of 157 rain gauge station.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.3
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• pp.122-134
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• 1994

The objective of this study is to provide with the hydrometeological and probabilistic characteristics of the storms and winds of typhoons that have been passed through the Korea peninsula during the last twenty-three years since 1961. The paths and intensities of the typhoons were analyzed. Fifty weather stations were selected and the rainfall and wind data during typhoon periods were collected. Rainfall data were analyzed for the patterns and probabilistic distributions. The results were presented to describe the areal distributions of probabilistic characteristics. Wind data were also analysed for their probabilistic distributions. The results obtained from this study can be summarized as follows: 1. The most frequent typhoon path that have passed through the Korean peninsula was type E, which was followed by types CWE, W, WE, and S. The most frequent typhoon intensity was type B, that was followed by A, super A, and C types, respectively. 2. The third quartile typhoon rainfall patterns appear most frequently followed by the second, first, and quartiles, respectively, in Seoul, Pusan, Taegu, Kwangju and Taejon. The single typhoon rainfalls with long rainfall durations tended to show delayed type rainfall patterns predominantly compared to the single rainfalls with short rainfall durations. 3. The most frequent probabilistic distribution for typhoon rainfall event is Pearson type-III, followed by Two-parameter lognormal distribution, and Type-I extremal distribution. 4. The most frequent probability distribution model of seashore location was Pearson type-III distribution. The most frequent probability distribution model of inland location was two parameter lognormal distribution. 5. The most frequent probabilistic distribution for typhoon wind events was Type-I xtremal distribution, followed by Two-parameter lognormal distribution, and Normal distribution.

• Ecology and Resilient Infrastructure
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• v.11 no.2
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• pp.55-64
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• 2024

The disaster impact assessment system was introduced in 2005 as a disaster prevention procedure for comprehensive and systematic developmental projects. However, according to the 'Practical Guidelines for Disaster Impact Assessment', Jeju Island's unique hydrogeological features necessitate the calculation of isohyetal-based probabilistic rainfall, which can reflect altitude, when estimating probabilistic rainfall for flood volume determination, rather than using conventional methods. Despite Jeju Island being centered around Hallasan, there are three Automatic Weather Stations (AWS) located at the summit of Hallasan, making weather stations denser than in other cities and provinces. Therefore, it is judged that there would be no difficulty in applying conventional methods, such as utilizing the probabilistic rainfall data from the weather stations or employing the Thiessen method, to estimate flood volumes for small-scale project areas. Accordingly, this study conducts a comparative analysis of the impact of applying general probabilistic rainfall from weather stations and isohyetal-based probabilistic rainfall in site in the context of Jeju Island's disaster impact assessment system.

• Journal of the Korean Geotechnical Society
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• v.35 no.12
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• pp.45-58
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• 2019

In this study, a stochastic analysis procedure based on numerical analysis was proposed to evaluate a kind of intensity-duration rainfall threshold for the initiation of slope failure due to rainfall infiltration. Fragility curves were generated as a function of rainfall intensity-duration from the results of probabilistic slope stability analysis by MCS considering the uncertainty of the soil shear strength, reflecting the results of infiltration analysis of rainfall over time. In the probabilistic analysis, slope stability analyses combined with the infiltration analysis of rainfall were performed to calculate the limit state function. Using the derived fragility curves, a chart showing the relationship between rainfall intensity and slope failure-time was developed. It is based on a probabilistic analysis considering the uncertainty of the soil properties. The proposed probabilistic failure distribution analysis could be beneficial for analyzing the time-dependent failure process of soil slopes due to rainfall infiltration, and for predicting when the slope failure should occur.

• Water for future
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• v.14 no.3
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• pp.47-54
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• 1981

The characteristics of point rainfall for three different durations in Seoul Pusan Taegu and Gwangju have been analysed by the probabilistic ainfall method and the M-year maximum rainfall method. The probabilities that the T-year probabilistic rainfall did not occur during the observation period, compared with the values obtained from the observed data. were smaller than the theoretical values. The averages of the probabilities that the M-year maximum-ten-minute rainfall did not occur in the consequent N-years were larger than the theoretical values, the M-year maximumone hour rainfall were smaller than the theoretical ones, and the M-year maximum daily rainfall nearly agreed with them, and while those of Japan were smaller than the theoretical values. It is recommended from the results that the recorded maximum value should be used as a design value rather than the probabilistic rainfall.

• Current Research on Agriculture and Life Sciences
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• v.15
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• pp.53-67
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• 1997

The objective of this study is to provide with the hydro-meteological and probabilistic characteristics of the storms of typhoons that have been passed through the Korean peninsula during the last twenty-three years since 1961. The paths and intensities of the typhoons were analyzed. Fifty weather stations were selected and the rainfall data during typhoon periods were collected. Rainfall data were analyzed for the patterns and probabilistic distributions. The results were presented to describe the areal distributions of probabilistic characteristics. The results obtained from this study can be summarized as follows: 1. The most frequent typhoon path that has passed through the Korean peninsula was type E, followed by types CWE, W, WE, and S. The most frequent typhoon intensity was type B, followed by A, super A, and e types, respectively. 2. The third quartile typhoon rainfall patterns appear most frequently followed by the second, first, and last quartiles, respectively, in Seoul, Pusan, Taegu, Kwangju and Taejon. The single typhoon rainfalls with long rainfall durations tended to show delayed type rainfall patterns predominantly compared to the single rainfalls with short rainfall durations. 3. The most frequent probabilistic distribution of typhoon rainfall event is Pearson type-III, followed by Two-parameter lognormal distribution, and Type-I extremal distribution. 4. The most frequent probability distribution model of seashore location was Pearson type-III distribution. The most frequent probability distribution model of inland location was two parameter lognormal distribution.

• Journal of Korea Water Resources Association
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• v.49 no.12
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• pp.995-1006
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• 2016

According to 5th IPCC Climate Change Report, there is a very high likelihood that the frequency and intensity of extreme rainfall events will increase. In reality, flood damage has increased, and it is necessary to estimate the future probabilistic design rainfall amount that climate change is reflected. In this study, the future probabilistic design precipitation amount is estimated by analyzing trends of future annual maximum daily rainfall derived by RCP 8.5 scenarios and using the scale-invariance technique. In the first step, after reviewing the time-scale characteristics of annual maximum rainfall amounts for each duration observed from 60 sites operating in Korea Meterological Administration, the feasibility of the scale-invariance technique are examined using annual daily maximum rainfall time series simulated under the present climate condition. Then future probabilistic design rainfall amounts for several durations reflecting the effects of climate change are estimated by applying future annual maximum daily rainfall time series in the IDF curve equation derived by scale-invariance properties. It is shown that the increasing trend on the probabilistic design rainfall amount has resulted on most sites, but the decreasing trend in some regions has been projected.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.155-167
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• 2017

Accurate QPE (Quantitative Precipitation Estimation) and the quality of the rainfall data for hydrological analysis are very important factors. Especially, the quality has a great influence on flood runoff result. It needs to know characteristics of the uncertainties in radar QPE for the reliable flood analysis. The purpose of this study is to present a probabilistic approach which defines the range of possible values or probabilistic distributions rather than a single value to consider the uncertainties in radar QPE and evaluate its applicability by applying it to radar rainfall. This study generated radar rainfall ensemble for the storms by the typhoon 'Sanba' on Namgang dam basin, Korea. It was shown that the rainfall ensemble is able to simulate well the pattern of the rain-gauge rainfall as well as to correct well the overall bias of the radar rainfall. The suggested ensemble technique represented well the uncertainties of radar QPE. As a result, the rainfall ensemble model by a probabilistic approach can provide various rainfall scenarios which is a useful information for a decision making such as flood forecasting and warning.

• The Korean Journal of Quaternary Research
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• v.19 no.2
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• pp.74-79
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• 2005

Recently, several attempts have been made to provide reasonable information on unusual severe weather phenomena such as tolerant heavy rains and very wild typhoons. Quantitative precipitation forecasts and probabilistic quantitative precipitation forecasts (QPFs and PQPFs, respectively) might be one of the most promising methodologies for early warning on the flesh floods because those diagnostic precipitation models require less computational resources than fine-mesh full-dynamics non-hydrostatic mesoscale model. The diagnostic rainfall model used in this study is the named QPM(Quantitative Precipitation Model), which calculates the rainfall by considering the effect of small-scale topography which is not treated in the mesoscale model. We examine the capability of probabilistic diagnostic rainfall model in terms of how well represented the observed several rainfall events and what is the most optimistic resolution of the mesoscale model in which diagnostic rainfall model is nested. Also, we examine the integration time to provide reasonable fine-mesh rainfall information. When we apply this QPM directly to 27 km mesh meso-scale model (called as M27-Q3), it takes about 15 min. while it takes about 87 min. to get the same resolution precipitation information with full dynamic downscaling method (called M27-9-3). The quality of precipitation forecast by M27-Q3 is quite comparable with the results of M27-9-3 with reasonable threshold value for precipitation. Based on a series of examination we may conclude that the proosed QPM has a capability to provide fine-mesh rainfall information in terms of time and accuracy compared to full dynamical fine-mesh meso-scale model.

• Journal of the Korean Geotechnical Society
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• v.30 no.10
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• pp.5-18
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• 2014

Many regions around the world are vulnerable to rainfall-induced slope failures. A variety of methods have been proposed for revealing the mechanism of slope failure initiation. Current analysis methods, however, do not consider the effects of non-homogeneous soil profiles and variable hydraulic responses on rainfall-induced slope failures. In this study, probabilistic stability analyses were conducted for weathered residual soil slopes with different soil thickness overlying impermeable bedrock to study the rainfall-induced failure mechanisms depending on the soil thickness. A series of seepage and stability analyses of an infinite slope based on one-dimensional random fields were performed to consider the effects of uncertainty due to the spatial heterogeneity of hydraulic conductivity on the failure of unsaturated slopes due to rainfall infiltration. The results showed that a probabilistic framework can be used to efficiently consider various failure patterns caused by spatial variability of hydraulic conductivity in rainfall infiltration assessment for a infinite slope.