• Journal of Korean Society of Water and Wastewater
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• v.35 no.6
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• pp.389-403
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• 2021

In this study, dual drainage system based runoff model was established for W-drainage area in G-si, and considering the various rainfall characteristics determined using Huff and Mononobe methods, the degree of flooding in the target area was analyzed and the risk was compared and analyzed through the risk matrix method. As a result, the Monobe method compared to the Huff method was analyzed to be suitable analysis for flooding of recent heavy rain, and the validity of the dynamic risk assessment considering the weight of the occurrence probability as the return period was verified through the risk matrix-based analysis. However, since the definition and estimating criteria of the flood risk matrix proposed in this study are based on the return period for extreme rainfall and the depth of flooding according to the results of applying the dual drainage model, there is a limitation in that it is difficult to consider the main factors which are direct impact on inland flooding such as city maintenance and life protection functions. In the future, if various factors affecting inland flood damage are reflected in addition to the amount of flood damage, the flood risk matrix concept proposed in this study can be used as basic information for preparation and prevention of inland flooding, as well as it is judged that it can be considered as a major evaluation item in the selection of the priority management area for sewage maintenance for countermeasures against inland flooding.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.5
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• pp.813-821
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• 2000

The engineering of satellite communication systems at frequencies above 10GHz requires a method for estimating rain-caused outage probabilities on the earth-satellite path. A procedure for predicting a rain attenuation distribution from a point rainfall rate distribution is, therefore, needed. In order to predict rain attenuation on the satellite link, several prediction models such as ITU-R, Global, SAM, DAH model, have been developed and used at a particular propagation condition, they may not be appropriate to a propagation condition in Korean territory. In this paper, a new rain attenuation prediction method appropriate to a propagation condition in Korea is introduced. Based on the results from ETRI measurements, a new method has been derived for an empirical approach with an identification on the horizontal correction factor as in current ITU-R method, and the vertical correction factor has been suggested with decreasing power law as a function of rainfall rate. This proposed model uses the entire rainfall rate distribution as input to the model, while the ITU-R and DAH model approaches only use a single 0.01% annual rainfall rate and assume that the attenuation at other probability levels can be determined from that single point distribution. This new model was compared with several world-wide prediction models. Based on the analysis, we can easily know the importance of the model choice to predict rain attenuation for a particular location in the radio communication system design.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.101-113
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• 2010

Recently actual rainfall pattern is decreasing rainy days and increasing in rainfall intensity and the frequency of flood occurrence is also increased. To consider recent situation, Engineers use deterministic methods like a PMP(Probable Maximum Precipitation). If design storm wouldn't occur, increasing of design criteria is extravagant. In addition, the biggest structure cause trouble with residents and environmental problem. And then it is necessary to study considering probability of rainfall parameter in each sub-basin for design of water structure. In this study, stochastic rainfall patterns are generated by using log-ratio method, Johnson system and multivariate Monte Carlo simulation. Using the stochastic rainfall patterns, hydrological analysis, hydraulic analysis and 2nd flooding analysis were performed based on GIS for their applicability. The results of simulations are similar to the actual damage area so the methodology of this study should be used about making a flood risk map or regidental shunting rout map against the region.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.47-56
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• 2004

The purpose of this study is to estimate soil loss amount according to the rainfall-runoff erosivity factor frequency and to analyze the hazard zone that has high possibilities of soil erosion in the watershed. RUSLE was used to analyze soil loss quantity. The study area is Gwanchon that is part of Seomjin river basin. To obtain the frequency rainfall-runoff erosivity factor, the daily maximum rainfall data for 39 years was used. The probability rainfall was calculated by using the Normal distribution, Log-normal distribution, Pearson type III distribution, Log-Pearson type III distribution and Extreme-I distribution. Log-Pearson type III was considered to be the most accurate of all, and used to estimate 24 hours probabilistic rainfall, and the rainfall-runoff erosivity factor by frequency was estimated by adapting the Huff distribution ratio. As a result of estimating soil erosion quantity, the average soil quantity shows 12.8 and $68.0ton/ha{\cdot}yr$, respectively from 2 years to 200 years frequency. The distribution of soil loss quantity within a watershed was classified into 4 classes, and the hazard zone that has high possibilities of soil erosion was analyzed on the basis of these 4 classes. The hazard zone represents class IV. The land use area of class IV shows $0.01-5.28km^2$, it ranges 0.02-9.06% of total farming area. Especially, in the case of a frequency of 200 years, the field area occupies 77.1% of total fanning area. Accordingly, it is considered that soil loss can be influenced by land cover and cultivation practices.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4B
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• pp.363-374
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• 2008

Intensity-Duration-Frequency (IDF) curve that is essential to calculate rainfall quantiles for designing hydraulic structures in Korea is generally formulated by regression analysis. In this study, IDF curve derived by the cumulative distribution function ("IDF by CDF") of the proper probability distribution function (PDF) of each site is suggested, and the corresponding parameters of IDF curve are computed using genetic algorithm (GA). For this purpose, IDF by CDF and the conventional IDF derived by regression analysis ("IDF by REG") were computed for 22 Korea Meteorological Administration (KMA) rainfall recording sites. Comparisons of RMSE (root mean squared error) and RRMSE (Relative RMSE) of rainfall intensities computed from IDF by CDF and IDF by REG show that IDF by CDF is more accurate than IDF by REG. In order to accommodate the effect of the recent intensive rainfall of Korea, the rainfall intensities computed by the two IDF curves are compared with that by at-site frequency analysis using the rainfall data recorded by 2006, and the result from IDF by CDF show the better performance than that from IDF by REG. As a result, it can be said that the suggested IDF by CDF curve would be the more efficient IDF curve than that computed by regression analysis and could be applied for Korean rainfall data.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.257-266
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• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

• Journal of Korean Society on Water Environment
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• v.26 no.5
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• pp.740-746
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• 2010

Rainwater has been used in many countries as a way of minimizing water availability problems. Rainwater harvesting system (RHS) has been successfully implemented as alternative water supply sources even in Korea. Although RHS is an effective alternative to water supply, its efficiency is often heavily influenced by temporal distribution of rainfall. Since natural precipitation is a random process and has probabilistic characteristics, it will be more appropriate to describe these probabilistic features of rainfall and its relationship with design storage capacity as well as supply deficit of RHS. This study presents the methodology to establish the relationships between storage capacities and deficit rates using probability distributions. In this study, the real three-story building was considered and nine scenaries were developed because the daily water usage pattern of the study one was not identified. GEV, Gumbel and the generalized logistic distribution ware selected according to the results of Kolmogorov-Smirnov test and Chi-Squared test. As a result, a set of curves describing the relationships under different exceedance probabilities were generated as references to RHS storage design. In case of the study building, the deficit rate becomes larger as return period increases and will not increase any more if the storage capacity becomes the appropriate quantity. The uncertainties between design storage and the deficit can be more understood through this study on the probabilistic relationships between storage capacities and deficit rates.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.413-413
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• 2011

강우의 공간분포에 대한 신뢰성 있는 추정은 수자원 해석 및 설계에 있어서 필수적인 요소이다. 강우장의 공간변동성에 대한 고해상도 추정은 홍수, 특히 돌발홍수의 원인이 되는 국지성 호우의 확인 및 분석에 있어서 중요하다. 또한 강우의 공간 변동성에 대한 고려는 면적평균강우량 추정의 정확도를 향상시키는데 있어서 중요하며, 강우-유출모델의 모의결과에 대한 신뢰도를 향상시키는데 큰 영향을 미친다. 최근 공간자료에 대한 공간분포예측에 있어서 공간상관성을 고려할 수 있는 공간통계학적 기법의 적용이 증가하고 있으며, 이러한 공간통계학적 기법의 적용에 있어서 신뢰성 있는 모델 매개변수의 추정 및 불확실성 평가는 공간분포 예측결과에 대한 신뢰성을 향상시키는데 중요한 역할을 한다. 외국의 경우 공간분포예측 및 모의, 매개변수의 불확실성 평가 등과 관련하여 활발한 연구가 이루어지고 있는 반면 국내 수자원 분야에서는 아직까지 활발한 연구가 이루어지고 있지 않은 실정이다. 따라서 본 연구에서는 계층구조로 구성된 가우시안 공간선형혼합모델을 적용하여 확률강우량의 공간분포를 추정함에 있어서 모델 매개변수에 대한 추정기법을 비교하였으며, 매개변수 추정기법으로서 경험베리오그램에 대한 곡선적합기법인 보통최소제곱법 및 가중최소제곱법, 우도함수를 기반으로 하는 최우도법 및 REML과 같은 기존의 매개변수 추정기법들과 최근 공간통계학 분야에서 적용이 증가하고 있는 Bayesian 기법을 비교하였다. 이로부터 매개변수 추정기법 간의 매개변수 추정치에 대한 정량적 비교결과를 제시하였으며, Bayesian 기법의 적용을 통해 매개변수에 대한 불확실성 추정결과를 제시하였다. 이러한 결과들은 확률강우량의 공간분포 추정에 있어서 공간예측모델의 매개변수 추정 및 예측에 대한 신뢰성을 향상시킬 수 있는 기초자료로 활용될 수 있을 것이다.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.887-893
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• 2018

In this study, the optimum design technology is suggested by using reliability analysis method. Nowadays, urban flood inundation is easily occurred because of local heavy rain. Traditional deterministic design method for storm sewer may underestimate the size of pipe. Therefore, stochastic method for the storm sewer design is necessary to solve this problem. In the present study, reliability model using FORM (First Order Reliability Method) was developed for the storm sewer. Developed model was applied to the real storm sewers of 5 different areas. Probability of exceeding capacity has been calculated and construction costs according to diameter have been compared. Probability of exceeding capacity of storm sewers of 5 areas have been calculated after estimating the return period of rainfall intensity.