• Magazine of the Korean Society of Agricultural Engineers
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• v.29 no.4
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• pp.59-72
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• 1987

Although long-term runoff analysis is important as much as flood analysis in the design of water works, the technological level of the former is relatively lower than that of the latter. In this respect, the precise estimation model for the volume of successive runoff should he developed as soon as possible. Up to now, in Korea, Gajiyama's formula has been widely used in long-term runoff analysis, which has many problems in applying in real situation. On the other hand, in flood analysis, unit hydrograph method has been exclusively used. Therefore, this study aims at trying to apply unit hydrograph method in long-term runoff analysis for the betterment of its estimation. Four test catchment areas were selected ; Maesan area in Namlum river as a representative area of Han river system, Cheongju area in Musim river as one of Geum river system, Hwasun area in Hwasun river as one of Yongsan river system, and Supyung area in Geum river as one of Nakdong river system. In the analysis of unit hydrograph, seperation of effective rainfall was carried out firstly. Considering that effective rainfall and moisture condition of catchrnent area are inside and outside of a phenomenon respectively and the latter is not considered in the analysis, Initial base flow(qb)was selected as an index of moisture condition. At the same time, basic equation(Eq.7) was established, in which qb can take a role as a parameter in relating between cumulative rainfall(P) and cumulative loss of rainfall(Ld). Based on the above equation, computer program for estimation model of qbwas seperately developed according to the range of qb, Developed model was applied to measured hydrographs and hyetographs for total 10 years in 4 test areas and effective rainfall was estimated. Estimation precision of model was checked as shown in Tab- 6 and Fig.8. In the next stage, based on the estimated effective rainfall(R) and runoff(Qd), a runoff distribution ratio was calculated for each teat area using by computerised least square method and used in making unit hydrographs in each test area. Significance of induced hydrographs was tested by checking the relative errors between estimated and measured runoff volume(Tab-9, 10). According to the results, runoff estimation error by unit hydrograph itself was merely 2 or 3 %, but other 2 or 3 % of error proved to be transferred error in the seperation of effective rainfall. In this study, special attentioning point is that, in spite of different river systems and forest conditions of test areas, standardized unit hydrographs for them have very similar curve shape, which can be explained by having similar catchinent characteristics such as stream length, catchinent area, slope, and vegetation intensity. That fact should be treated as important factor ingeneralization of unit hydrograph method.

• Journal of the Korean Geotechnical Society
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• v.30 no.6
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• pp.51-59
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• 2014

Shallow landslides and debris flows are a common form of soil slope instability in South Korea. These events may be generally initiated as a result of intense rainfall or lengthening rainfall duration because of the effects of climate change. This paper presents the evaluation of rainfall-induced natural soil slope stability and reinforced soil slope instability under vertical load (railway or highway load) throughout South Korea based on quantitative analysis obtained from 58 sites rainfall observatories for 38 years. The slope stability was performed for infinite and geogrid-reinforced soil slopes by taking an average of maximum rainfall every ten years from 1973 to 2010. Seepage analysis is carried out on unsaturated soil slope using the maximum rainfall at each site, and then the factor of safety was calculated by coupled analysis using saturated and unsaturated strength parameters. The contour map of South Korea shows four stages in 10-year-time for the degree of landslide hazard. The safety factor map based on long term observational data will help prevent rainfall-induced soil slope instability for appropriate design of geotechnical structures regarding disaster protection.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.183-190
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• 1993

It is desirable to utilize the result after studying the rainfall characteristics including the latest observation data in the districts for the sake of establishment of the more accurate plans for drainage or plans for hydraulic stuctures because the rainfall phenomena are different in their characteristics by regional groups and if we make a meteorological observation for a long period of time, the rainfall characteristics also change a great deal as compared with the preceding years. Therefore, we selected only the annual maximum rainfall from the self-recording rain gauge of the main rainfall observation station (Cheju, Sogwipo, Songsanpo) in the Cheju districts in the last twenty years, extracted the rainfall by actual measurement by the rainfall duration, and induced the optimal probable rainfall-intensity formulas by regional groups in the Cheju districts, taking advantage of the rainfall formulas being in wide use in general, that is, Talbot type, Sherman type, Japanese type, and new Semi-log type. As the result, the return periods at Cheju station appeared to be three years to five years and the optimal probable rainfall-intensity formula at Cheju station, Japanese type and outside the city, Talbot type; Sogwipo, Sherman type; Songsanpo, Talbot type respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3287-3295
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• 2009

This present study implemented a rainfall simulation system, and performed simulation and numerical analysis according to rainfall and slope conditions using a model slope built with weathered granite soil. Extensive analysis were conducted on the characteristics of changes in volumetric water content and pore water pressure measured in the simulation, and compared them with the results of numerical analysis. It took longer for the volumetric water content to reach the limit when rainfall intensity was high and the slope was steep and shorter when rainfall intensity was low and the slope was gentle. When rainfall intensity was low and the duration of rainfall was short, negative pore water pressure was higher and the time for restoration was shorter. On the contrary, when rainfall intensity was high and the duration of rainfall was long, it took a longer time to restore negative pore water pressure. In the results of rainfall simulation and numerical analysis, the distribution of volumetric water content and pore water pressure was similar between the two. However, the volumetric water content was different by up to 5%, and pore water pressure by up to 3kPa.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.6
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• pp.3-12
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• 2008

It is important to estimate accurate effective rainfall to analyse flood flow and long-term runoff for the rational planning, design, and management of water resource. The initial abstraction is also important to estimate effective rainfall. The Soil Conservation Service (SCS) has developed a procedure and it has been most commonly applied to estimate effective rainfall. But the SCS method still has weak points, because of unnatural assumptions such as antecedent moisture conditions and initial abstraction. The coefficient of initial abstraction(K) is depending on the soil moisture condition and antecedent rainfall. The maximum storage capacity of Umax which is calibrated by stream flow data in the proposed watershed was derived from the DAWAST(DAily WAtershed STreamflow) model. The values of K obtained from 69 storm events at the five watersheds are ranging from 0.133 to 0.365 and its mean value is 0.207. Effective rainfall could be estimated more reasonably by introducing new concept of initial abstraction. The equation of $K=0.076Sa^{0.255}$ was recommended instead of 0.2 and it could be applicable to the small-medium rural watersheds.

• Journal of the Korean Professional Engineers Association
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• v.18 no.2
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• pp.1-5
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• 1985

In the flood prediction research, it is pointed out that the difficulty of flood prediction is the frequently experienced overestimation of flood peak. That is caused by the rainfall prediction difficulty and the nonlinearity of hydrological phenomena. Even though the former reason will remain still unsolved, but the latter one can be possibly resolved the method of the AMRA (Auto Regressive Moving Average) model for each runoff component as developed by Dr. Hino and Dr. Hasebe. The principle of the method consists of separating though the numerical filters the total runoff time series into long-term, intermediate and short-term components, or ground water flow, interflow, and surface flow components. As a total system, a hydrological system is a non-linear one. However, once it is separated into two or three subsystems, each subsystem may be treated as a linear system. Also the rainfall components into each subsystem a estimated inversely from the runoff component which is separated from the observed flood. That is why flood prediction can be done without rainfall data. In the prediction of surface flow, the Kalman filter will be applicable but this paper shows only impulse function method.

• Journal of Korean Society on Water Environment
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• v.23 no.6
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• pp.829-836
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• 2007

For the purpose of managing non-point sources, water quality control basins (WQCBs) are often designed to capture rainfall events smaller than extreme events. The design rainfall statistics and runoff capture rates for sizing a WQCB should be derived from the local long-term continuous rainfall record. In this study, the 31-year continuous rainfall data recorded in Busan is analyzed to derive the synthesized runoff capture curve incorporated with SCS curve number.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.1
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• pp.115-120
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• 1993

The study is to derive a typical probable rainfall intensity formula(TPRIF) by analyzing pre-issued probable rainfall intensity formulas (PPRIF) over principal rainfall observation stations, and to obtain the regional characteristics based on the rainfall patterns by evaluating probable rainfall amount. The conclusions are as follows. A TPRIF which integrates PPRIF with a single pattern is presented. In deriving probable rainfall intensity, the application of TPRIF was more excellent than that of PPRIF. The value of R24/Rl which is the dimensionless ratio for rainfall characteristics tends to be inversely proportionate to the regional coefficient n. By comparing these values, the whole country could be divided into about 5 regions. In these five regions, the short-duration rainfall intensity is dominant in inland areas but the long-duration rainfall intensity is dominant in East Sea areas.

• Atmosphere
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• v.32 no.1
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• pp.1-15
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• 2022

Recently, Japan's Meteorological Research Institute presented the d4PDF database (Database for Policy Decision-Making for Future Climate Change, d4PDF) through large-scale climate ensemble simulations to overcome uncertainty arising from variability when the general circulation model represents extreme-scale precipitation. In this study, the change of precipitation characteristics between the historical and future climate conditions in the Yongdam-dam basin was analyzed using the d4PDF data. The result shows that annual mean precipitation and seasonal mean precipitation increased by more than 10% in future climate conditions. This study also performed an analysis on the change of the return period rainfall. The annual maximum daily rainfall was extracted for each climatic condition, and the rainfall with each return period was estimated. In this process, we represent the extreme-scale rainfall corresponding to a very long return period without any statistical model and method as the d4PDF provides rainfall data during 3,000 years for historical climate conditions and during 5,400 years for future climate conditions. The rainfall with a 50-year return period under future climate conditions exceeded the rainfall with a 100-year return period under historical climate conditions. Consequently, in future climate conditions, the magnitude of rainfall increased at the same return period and, the return period decreased at the same magnitude of rainfall. In this study, by using the d4PDF data, it was possible to analyze the change in extreme magnitude of rainfall.