• Journal of Korea Water Resources Association
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• v.35 no.2
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• pp.173-186
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• 2002

Rainfall-runoff model is usually used in estimating the design flood, and the most important elements in this model are probable rainfall and unit hydrograph. So, it is the most important step to estimate probable rainfall reasonably and exactly. If a basin area exceeds a certain scale, probable areal rainfall should be used as probable rainfall, but, Probable point- mean rainfall be usually used in Korea. Consequently, probable rainfall is used too high and unit hydrograph is used relatively too low. Thus the improvement is unavoidable. So, in this study, the parameters are proposed that transform the 1day, 2day rainfall to 24hr, 48hr rainfall, and areal rainfall data series are composed by using the same time rainfall data. Also, the areal reduction factor(ARF) is developed as the increase of area by the calculated probable point mean rainfall and probable areal rainfall by frequency analysis in Han-River basin. It can be the measure to easily transform probable point- mean rainfall to probable areal rainfall.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.821-831
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• 2014

Stochastic rainfall generators or stochastic simulation have been widely employed to generate synthetic rainfall sequences which can be used in hydrologic models as inputs. The calibration of Poisson cluster stochastic rainfall generator (e.g. Modified Bartlett-Lewis Rectangular Pulse, MBLRP) is seriously affected by local minima that is usually estimated from the local optimization algorithm. In this regard, global optimization techniques such as particle swarm optimization and shuffled complex evolution algorithm have been proposed to better estimate the parameters. Although the global search algorithm is designed to avoid the local minima, reliable parameter estimation of MBLRP model is not always feasible especially in a limited parameter space. In addition, uncertainty associated with parameters in the MBLRP rainfall generator has not been properly addressed yet. In this sense, this study aims to develop and test a Bayesian model based parameter estimation method for the MBLRP rainfall generator that allow us to derive the posterior distribution of the model parameters. It was found that the HBM based MBLRP model showed better performance in terms of reproducing rainfall statistic and underlying distribution of hourly rainfall series.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.773-784
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• 2014

This study evaluated the applicability of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) rainfall generation model for modeling extreme rainfalls and floods in Korean Peninsula. Firstly, using the ISPSO (Isolated Species Particle Swarm Optimization) method, the parameters of the MBLRP model were estimated at the 61 ASOS (Automatic Surface Observation System) rain gauges located across Korean Peninsula. Then, the synthetic rainfall time series with the length of 100 years were generated using the MBLRP model for each of the rain gauges. Finally, design rainfalls and design floods with various recurrence intervals were estimated based on the generated synthetic rainfall time series, which were compared to the values based on the observed rainfall time series. The results of the comparison indicate that the design rainfalls based on the synthetic rainfall time series were smaller than the ones based on the observation by 20% to 42%. The amount of underestimation increased with the increase of return period. In case of the design floods, the degree of underestimation was 31% to 50%, which increases along with the return period of flood and the curve number of basin.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1976-1981
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• 2011

In this study, the optimal sewer layout model(Lee, J.H., 2010)[1] was applied to verify the reduction effect of urban inundation in the optimal sewer networks, which designed by this optimal model, for various artificial rainfall events in urban areas. Then the optimal model was developed by Lee, J.H. to minimize the peak outflow at outlet in sewer network. The applied rainfall events are two types. One is the rainfall event which the double peak occurs between specific time distance continuously. The other is the continuous rainfall event with specific rainfall intensity. As the result, in two applied rainfall types, the peak outflows at outlet were reduced in the optimal sewer networks which designed the optimal sewer layout model of Lee, J.H.. Therefore, the peak outflow is reduced because the inflows at each manhole are distributed in the whole sewer networks, it's not delay of inflows by this optimal model.

• Journal of Korean Society of Disaster and Security
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• v.8 no.2
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• pp.21-26
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• 2015

This study analyzes the failure predict of model slope due to changes in ground condition followed by heavy rainfall with a simulated rainfall system. the movement of a slope from the rainfall penetrating the unsaturated soil is investigated with respect to various conditions of pore-water pressure, earth pressure and moisture content, considering rainfall duration and permeability.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.180-180
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• 2015

Weather radar has been widely used in measuring precipitation and discharge and predicting flood risks. The radar rainfall estimate has one of the essential problems in terms of uncertainty and accuracy. Previous study analyzed radar errors to reduce its uncertainty or to improve its accuracy. Furthermore, a recent analyzed the effect of radar error on rainfall-runoff using spatial error model (SEM). SEM appropriately reproduced radar error including spatial correlation. Since the SEM does not take the time dependence into account, its time variability was not properly investigated. Therefore, in the current study, we extend the SEM including time dependence as well as spatial dependence, named after Spatial-Temporal Error Model (STEM). Radar rainfall events generated with STEM were tested so that the peak runoff from the response of a basin could be investigated according to dependent error. The Nam River basin, South Korea, was employed to illustrate the effects of STEM on runoff peak flow.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.773-783
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• 2009

The effects of rainfall input uncertainty on predictions of stream flow are studied based extended GLUE (Generalized Likelihood Uncertainty Estimation) approach. The uncertainty in the rainfall data is implemented by systematic/non-systematic rainfall measurement analysis in Weida catchment, Germany. PDM (Probability Distribution Model) rainfall runoff model is selected for hydrological representation of the catchment. Using general correction procedure and DUE(Data Uncertainty Engine), feasible rainfall time series are generated. These series are applied to PDM in MC(Monte Carlo) and GLUE method; Posterior distributions of the model parameters are examined and behavioural model parameters are selected for simplified GLUE prediction of stream flow. All predictions are combined to develop ensemble prediction and 90 percentile of ensemble prediction, which are used to show the effects of uncertainty sources of input data and model parameters. The results show acceptable performances in all flow regime, except underestimation of the peak flows. These results are not definite proof of the effects of rainfall uncertainty on parameter estimation; however, extended GLUE approach in this study is a potential method which can include major uncertainty in the rainfall-runoff modelling.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.209-219
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• 2022

To experimentally investigate the variation of soil characteristics in slope during rainfall and the shape of slope failure, the model test was performed using soil box and artificial rainfall simulator. The model test of slope formed by the homogenous sand was performed, and the saturation pattern in the model slope due to rainfall infiltration was observed. The slope model with the inclination of 35° was set up on the slope of 30°, and the rainfall intensity of 50 mm/hr was applied in the test. The soil depth of 35 cm was selected by considering the size of soil box, and the TDR (time domain reflectometry) sensors were installed at various depths to investigate the change of soil characteristics with time. As the result of model test, the slope model during rainfall was saturated from the soil surface to the subsurface, and from the toe part to the crest part due to rainfall infiltration. That is, the toe part of slope was firstly saturated by rainfall infiltration, and then due to continuous rainfall the saturation range was enlarged from the toe part to the crest part in the slope model. The failure of slope model was started at the toe part of slope and then enlarged to the crest part, which is called as the retrogressive failure. At the end of slope failure, the collapsed area increased rapidly. Also, the mode of slope failure was rotational. Meanwhile, the slope failure was occurred when the matric suction in the slope was reached to the air entry value (AEV) estimated in soil-water characteristic curve (SWCC).

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.146-146
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• 2022

A flash flood is one of the most hazardous natural events caused by heavy rainfall in a short period of time in mountainous areas with steep slopes. Early warning of flash flood is vital to minimize damage, but challenges remain in the enhancing accuracy and reliability of flash flood forecasts. The forecasters can easily determine whether flash flood is occurred using the flash flood guidance (FFG) comparing to rainfall volume of the same duration. In terms of this, the hydrological model that can consider the basin characteristics in real time can increase the accuracy of flash flood forecasting. Also, the predicted radar rainfall has a strength for short-lead time can be useful for flash flood forecasting. Therefore, using both hydrological models and radar rainfall forecasts can improve the accuracy of flash flood forecasts. In this study, FFG was applied to simulate some flash flood events in the Taehwa river basin by using of SURR model to consider soil moisture, and applied to the flash flood forecasting using predicted radar rainfall. The hydrometeorological data are gathered from 2011 to 2021. Furthermore, radar rainfall is forecasted up to 6-hours has been used to forecast flash flood during heavy rain in August 2021, Wulsan area. The accuracy of the predicted rainfall is evaluated and the correlation between observed and predicted rainfall is analyzed for quantitative evaluation. The results show that with a short lead time (1-3hr) the result of forecast flash flood events was very close to collected information, but with a larger lead time big difference was observed. The results obtained from this study are expected to use for set up the emergency planning to prevent the damage of flash flood.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.1
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• pp.9-15
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• 2013

This study is to evaluate the parameter behavior of VfloTM distributed rainfall-runoff model by applying 3 kinds of rainfall interpolation methods viz. Inverse Distance Weighting (IDW), Kriging (KRI), and Thiessen network (THI). For the 1,544 $km^2$ Dongcheon watershed of Nakdong river, the model was calibrated using 4 storm events in 2007 and 2009, and validated using 2 storm events in 2010. The model was calibrated with Nash-Sutcliffe model efficiency of 0.97 for IDW, 0.94 for KRI, and 0.95 for THI respectively. For the sensitive parameters, the saturated hydraulic conductivity ($K_{sat}$) for IDW, KRI, and THI were 0.33, 0.31, and 0.43 cm/hr, and the soil suction head at the wetting front (${\Psi}_f$) were 4.10, 3.96, and 5.19 cm $H_2O$ respectively. These parameters affected the infiltration process by the spatial distribution of antecedent moisture condition before a storm.