• Journal of Korea Water Resources Association
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• v.53 no.11
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• pp.1039-1047
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• 2020

Atmospheric rivers, which transport large amount of water vapor from mid-latitude to the inland, are an important driving force of water cycle and extreme hydrologic phenomenas. The main objective of this study is to analyze the hydrological impact of the AR landfalls on the Korean Peninsula in 2000 - 2015. The result showed that the AR is closely related to the characteristics of precipitation, water level and runoff in the Korean Peninsula. The landfalls of the AR affected about 57% of annual precipitation on the Korean Peninsula, and had a greatest impact on the summer rainfall. It also affected the water level and runoff at the five major rivers of Korea, and water levels exceeding the thresholds of flood warning were observed when the AR landed. Moreover, it was found that the runoff above the third quartile with AR landfalls. These results suggest that the AR not only has a significant influence on the hydrological characteristics of the Korean Peninsula, but also have a close relationship with the extreme hydrological events like floods. The results of this study are expected to be used as the reference for the analysis of the impact of the AR on the various fields in the Korean Peninsula.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• Journal of Environmental Science International
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• v.22 no.5
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• pp.571-580
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• 2013

In this study, compared with the result of water surface elevation and water velocity on the establishment of river maintenance basic plan and result of HEC-GeoRAS based GIS, and after use the result of water surface elevation and velocity were observed in the Han stream on Jeju island, analysis 2 dimensional stream flow. the lateral hydraulic characteristics and curved channel of the stream were analyzed by applying SMS-RMA2 a 2 dimensional model. The results of the analysis using HEC-RAS model and HEC-GeoRAS model indicated that the distribution ranges of water surface elevation and water velocity were similar, but the water surface elevation by section showed a difference of 0.7~2.18 EL.m and 0.63~1.16 EL.m respectively, and water velocity also showed differences of maximum 1.58m/sec and 2.67m/sec. SMS-RMA2 analysis was done with the sphere of Muifa the typhoon as a boundary condition, and as a result, water velocity distribution was found to be 1.19 through 3.91 m/sec, and the difference of lateral water velocity in No. 97 through 99 the curved channel of the stream was analyzed to be 1.59 through 2.36 m/sec. In conclusion it is anticipated that the flow analysis of 2 dimension model of stream can reflect the hydraulic characteristics of the stream curved channel or width and shape, and can be applied effectively in the establishment of river maintenance basic plan or management and designing of stream.

• Water for future
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• v.28 no.5
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• pp.117-127
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• 1995

The application and analysis for the scale considering GIUH model proposed by the authors in this issue have been performed for the leemokjung sub-basin in the Pyungchang basin one of IHP representative basin in Korea. Scales of topographic maps for model application and fractal analysis are 1:25,000, 1:50,000 and 1:100,000. The ratio between successive scales is therefore constant. Link lengths were measured using a curvimeter with the resolution of 1 mm. Richardson's method was employed to have fractal dimension of streams. Apparent alternations of parameters were found in accordance with variations of map scale. And this tendency could mislead physical meanings of parameters because model parameters had to preserve their own value in spite of map scale change. It was found that uses of fractal transform and Melton's law could help to control the scale problem effectively. This methodlogy also could emphasize the relationship between network and basin to the model. To verify the applicability of GIUH proposed in this research, the model was compared with the exponential GIUH model. It is proven that proposed 2-parameter gamma GIUH model can better simulate the corresponding runoff from any given flood events than exponential GIUH model. The result showed that 2-parameter gamma GIUH model and fractal theory could be used for deriving scale considered IUH of the basin.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.659-672
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• 2001

Generally, design flood for a hydraulic structure is estimated using statistical analysis of runoff data. However, due to the lack of runoff data, it is difficult that the statistical method is applied for estimation of design flood. In this case, the synthetic unit hydrograph method is used generally and the models such as NYMO method, Snyder method, SCS method, and HYMO method have been widely used in Korea. In this study, these methods and KICT method, which is developed in year 2000, are compared and analyzed in 10 study areas. Firstly, peak flow and peak time of representative unit hydrograph and synthetic unit hydrograph in study area are compared, and secondly, the shape of unit hydrograph is compared using a root mean square error(RMSE). In Nakayasu method developed in Japan, synthetic unit hydrograph is very different from peak flow, peak time, and the shape of representative unit hydrograph, and KICT method(2000) is superior to others. Also, KICT method(2000) is superior to others in the aspects of using hydrologic and topographical data. Therefore, Nakayasu method is not a proper in hydrological practice. Moreover, it is considered that KICT model is a better method for the estimation of design flood. However, if other model, i.e. SCS method, Nakayasu method, and HYMO method, is used, parameters or regression equations must be adjusted by analysis of real data in Korea.

• Journal of Environmental Science International
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• v.20 no.6
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• pp.783-788
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• 2011

Different from the main land of South Korea, Jeju Island has been in difficulties for measuring discharge. Due to high infiltration rate, most of streams in Jeju Island are usually in the dried state except six streams with the steady base flow, and the unique geological characteristics such as steep slope and short traveling distance of runoff have forced rainfall runoff usually to occur during very short period of time like one or two days. While discharge observations in Jeju Island have been conducted only for 16 sites with fixed electromagnetic surface velocimetry, effective analysis and validation of observed discharge data and operation of the monitoring sites still have been limited due to very few professions to maintain such jobs. This research is sponsored by Ministry of Land, Transport and Maritime Affairs to build water cycle monitoring and management system of Jeju Island. Specifically, the research focuses on optimizing discharge measurement techniques adjusted for Jeju Island, expanding the monitoring sites, and validating the existing discharge data. First of all, we attempted to conduct discharge measurements in streams with steady base flow, by utilizing various recent discharge monitoring techniques, such as ADCP, LSPIV, Magnetic Velocimetry, and Electromagnetic Wave Surface Velocimetry. ADCP has been known to be the most accurate in terms of discharge measurement compared with other techniques, thus that the discharge measurement taken by ADCP could be used as a benchmark data for validation of others. However, there are still concerns of using ADCP in flood seasons; thereby LSPIV would be able to be applied for replacing ADCP in such flooded situation in the stream. In addition, sort of practical approaches such as Magnetic Velocimetry, and Electromagnetic Wave Surface Velocimetry would also be validated, which usually measure velocity in the designated parts of stream and assume the measured velocity to be representative for whole cross-section or profile at any specified location. The result of the comparison and analysis will be used for correcting existing discharge measurement by Electromagnetic Wave Surface Velocimetry and finding the most optimized discharge techniques in the future.

• Journal of Korea Water Resources Association
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• v.41 no.1
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• pp.17-25
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• 2008

Whether rating curves are used in practice or new ones are derived, the characteristics of regression analysis are often neglected. For example, a discharge rating curve, which is established from a regression of observed water levels (H) on observed flowrates(Q), is sometimes used for estimating a design water level corresponding to a simulated design flood runoff. However, if independent and dependent variables are changed with each other, the regression equation is changed in existing regression analysis, which is derived from vertical errors between observed data and regression line. Thus, regression equations should not be applied inversely. To avoid this problem, A new two-way variable least-squares regression analysis is proposed. The new method was applied to the rating curves of five water level stations on main stream of Nakdong River. The three kinds of regression models, which are respectively regression of Q versus H (model 1), H versus Q (model 2) and two-way (model 3), showed that the new method can reduce inadvertent mistakes when applied in practice.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.93-102
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• 2009

A prediction of streamflow based on multi-objective function is presented to check the performance of Probability Distributed Model(PDM) in Miho stream basin, Chungcheongbuk-do, Korea. PDM is a lumped conceptual rainfall runoff model which has been widely used for flood prevention activities in UK Environmental Agency. The Monte Carlo Analysis Toolkit(MCAT) is a numerical analysis tools based on population sampling, which allows evaluation of performance, identifiability, regional sensitivity and etc. PDM is calibrated for five model parameters by using MCAT. The results show that the performance of model parameters(cmax and k(q)) indicates high identifiability and the others obtain equifinality. In addition, the multi-objective function is applied to PDM for seeking suitable model parameters. The solution of the multi-objective function consists of the Pareto solution accounting to various trade-offs between the different objective functions considering properties of hydrograph. The result indicated the performance of model and simulated hydrograph are acceptable in terms on Nash Sutcliffe Effciency*(=0.035), FSB(=0.161), and FDBH(=0.809) to calibration periods, validation periods as well.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.13-23
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• 2021

This study intended to assess the reliability of topographic data using satellite imaging data. The topographical data using actual instrumentation data and satellite image data were established and applied to the rainfall-leak model, S-RAT, and the topographical data and outflow data were compared and analyzed. The actual measurement data were collected from the Water Resources Management Information System (WAMIS), and satellite image data were collected from MODIS observation sensors mounted on Terra satellites. The areas subject to analysis were selected for two rivers with more than 80% mountainous areas in the Han River basin and one river basin with more than 7% urban areas. According to the analysis, the difference between instrumentation data and satellite image data was up to 50% for peak floods and up to 17% for flood totals in rivers with high mountains, but up to 13% for peak floods and up to 4% for flood totals. The biggest difference in the video data is Landuse, which shows that MODIS satellite images tend to be recognized as cities up to 60% or more in urban streams compared to WAMIS instrumentation data, but MODIS satellite images are found to be less than 5% error in forest areas.

• Journal of Korea Water Resources Association
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• v.56 no.1
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• pp.53-62
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• 2023

Recently, due to the influence of climate change, the occurrence of damage to heavy rain is increasing around the world, and the frequency of heavy rain with a large amount of rain in a short period of time is also increasing. Heavy rains generate a large amount of outflow in a short time, causing flooding in the downstream part of the mountainous area before joining the small and medium-sized rivers. In order to reduce damage to downstream areas caused by flooding, it is very important to calculate the outflow of mountainous areas due to torrential rains. However, the sewage network flooding analysis, which is currently conducting the most analysis in Korea, uses the time and area method using the existing data rather than calculating the rainfall outflow in the mountainous area, which is difficult to determine that the soil characteristics of the region are accurately applied. Therefore, if the rainfall is analyzed for mountainous areas that can cause flooding in the downstream area in a short period of time due to large outflows, the accuracy of the analysis of flooding characteristics that can occur in the downstream area can be improved and used as data for evacuating residents and calculating the extent of damage. In order to calculate the rainfall outflow in the mountainous area, the rainfall outflow in the mountainous area was calculated using MIKE SHE among the MIKE series, and the flooding analysis in the downstream area was conducted through MIKE 21 FM (Flood model). Through this study, it was possible to confirm the amount of outflow and the time to reach downstream in the event of rainfall in the mountainous area, and the results of this analysis can be used to protect human and material resources through pre-evacuation in the downstream area in the future.