• Journal of Korea Water Resources Association
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• v.43 no.2
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• pp.211-220
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• 2010

The objective of this paper presents the application of an "integrated urban flood modeling-runoff model, urban flood model and sewer system model-" in a highly urbanized area of Samcheok where is seriously inundated in 2002 and 2003. For this, we demonstrate how couple a 1-D hydrodynamic model of the river, a 2-D hydrodynamic model of the overland (surface) flow, and a sewer network model including each boundary conditions. In order to make data file for the model, topographic information like elevation and share rate of buildings are directly extracted from DEM or topographical source data without data exchange to avoid uncertainty errors. Furthermore, the research is to assess the impacts of Manning n and buildings influences to inundated depth by changing its share ratio from 10 % to 30 % in low-land urban area. As a results, we found out that the urban inundated depth was decreased by Manning n but increased by buildings ratio. The calculated results of inundation was similar with observed one in 2002 and 2003 flooding. Furthermore, the area was also inundated under not riverbank break case in 2002 flooding.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.557-565
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• 2016

The risk of collapse in hydraulic structures has become more elevated, due to the increased probability and scale of flooding caused by global warming and the resulting abnormal climatic conditions. When a levee, a typical hydraulic structure, breaks, an enormous breach flow pours into the floodplain and much flood damage then occurs. It is important to accurately calculate the breach discharge in order to predict this damage. In this study, the variation of the breach discharge with the asymmetry in the cross-section of the levee breach was analyzed. Through hydraulic experiments, the cross-section of the breach was analyzed during the collapse using the BASD (Bilateral ASymmetry Degree), which was developed to measure the degree of asymmetry. The relationship of the breach discharge was identified using the BASD. Additionally, the variation of the breach flow measured by the BASD was investigated through a 3-D numerical analysis under the same flow conditions as those in the experiment. It was found that the assumption of a rectangular breach cross-section, which is generally used for the estimation of the inundation area, can cause the breach discharge to be overestimated. According to the BASD, the breach flow is decreased by the interference effect in the breach section of the levee. If the breach flow is calculated while considering the BASD in the numerical analysis of the flooding, it is expected that the predicted inundation area can be estimated accurately.

• 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 Korea Water Resources Association
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• v.52 no.5
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• pp.361-372
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• 2019

The purpose of this study is to develop a two-dimensional land surface flood analysis model based on uniform square grid using the governing equations except for the convective acceleration term in the momentum equation. Finite volume method and implicit method were applied to spatial and temporal discretization. In order to reduce the execution time of the model, parallel computation techniques using CPU were applied. To verify the developed model, the model was compared with the analytical solution and the behavior of the model was evaluated through numerical experiments in the virtual domain. In addition, inundation analyzes were performed at different spatial resolutions for the domestic Janghowon area and the Sebou river area in Morocco, and the results were compared with the analysis results using the CAESER-LISFLOOD (CLF) model. In model verification, simulation results were well matched with the analytical solution, and the flow analyses in the virtual domain were also evaluated to be reasonable. The results of inundation simulations in the Janghowon and the Sebou river area by this study and CLF model were similar with each other and for Janghowon area, the simulation result was also similar to the flooding area of flood hazard map. The different parts in the simulation results of this study and the CLF model were compared and evaluated for each case. The results of this study suggest that the model proposed in this study can simulate the flooding well in the floodplain. However, in case of flood analysis using the model presented in this study, the characteristics and limitations of the model by domain composition method, governing equation and numerical method should be fully considered.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.459-467
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• 2016

LISFLOOD-FP model in which channel flows are resolved separately from the floodplain flows using either a kinematic or diffusive wave approximation has been used to analyze flooding behavior on the lower Mankyung River influenced by backwater. A calibration and validation process was applied using the previous flood events to assess the model performance. Sensitivity analysis was conducted for main calibrated parameters, such as Manning roughness coefficient and downstream boundary condition. Also, we examined the effect of warm-up for the initial conditions. The results show that the computed hydrograph is in good agreement with measured data on the study reach, even though it was a hydrologic kinematic wave model. The sensitive analysis show that the difference between the computed results may be greater depending on the used calibrated parameters and that the sufficient calibration/validation process against various flood events is necessary. If the flood inundation simulation is performed using the validated model, it is expected to be able to contribute about river planning and policy decision-making for flood damage reduction.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.259-266
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• 2023

Global climate change is increasing, and the damage and scale of localized torrential rains are increasing. Pre-flood analysis simulation results should be derived from rainfall data through rainfall forecasts to prevent flood damage. In addition, it is necessary to control the use and management of flood response disaster prevention facilities through immediate decision-making. However, methods using spills and flood models such as XPSWMM and GATE2018 are limited due to professional usability and complex analytical procedures. Prototype (flood disaster prevention facility simulator) of this study is developed by calculating rainfall (short-term and long-term) using CBD software development methods. It is also expected to construct administrator and user-centric interfaces and provide GIS and visible data (graphs, charts, etc.).

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.519-528
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• 2016

Frequently torrential rain is occurred by climate change and urbanization. Urban is formed with road, residential and underground area. Without detailed topographic flooded analysis consideration can take a result which are wrong flooded depth and flooded area. Especially, flood analysis error of population and assets in dense downtown is causing a big problem for establishments and disaster response of flood measures. It can lead to casualties and property damage. Urban flood analysis is divided into sewer flow analysis and surface inundation analysis. Accuracy is very important point of these analysis. In this study, to confirm the effects of the elevation data precision in the process of flooded analysis were studied using 10m DEM, LiDAR data and 1:1,000 digital map. Study area is Dorim-stream basin in the Darim drainage basin, Sinrim 3 drainage basin, Sinrim 4 drainage basin. Flooding simulation through 2010's heavy rain by using XP-SWMM. Result, from 10m DEM, shows wrong flood depth which is more than 1m. In particular, some of the overflow manhole is not seen occurrence. Accordingly, detailed surface data is very important factor and it should be very careful when using the 10m DEM.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.51-65
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• 2010

We suggest a simple and practical flood forecasting and warning system, which can predict change in the water level of a river in a small to medium-size watershed where flash flooding occurs in a short time. We first choose the flood defense target points, through evaluation of the flood risk of dike overflow and lowland inundation. Using data on rainfall, and on the water levels at the observed and prediction points, we investigate the interrelations and derive a regression formula from which we can predict the flood level at the target points. We calculate flood water levels through a calibrated flood simulation model for various rainfall scenarios, to overcome the shortage of real water stage data, and these results as basic population data are used to derive a regression formula. The values calculated from the regression formula are modified by the weather condition factor, and the system can finally predict the flood stages at the target points for every leading time. We also investigate the applicability of the prediction procedure for real flood events of the Jungnang Stream basin, and find the forecasting values to have close agreement with the surveyed data. We therefore expect that this suggested warning scheme could contribute usefully to the setting up of a flood forecasting and warning system for a small to medium-size river basin.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1797-1807
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• 2013

Dams always have the possibility of failure due to unexpected natural phenomena. In particular, dam failure can cause huge damage including damage for humans and properties when dam downstream regions are densely populated or have important national facilities. Although many studies have been conducted on the analysis of flood waves about single dam failure thus far, studies on the analysis of flood waves about the sequential failure of dams are lacking. Therefore, the purpose of this study was to calculate the peak discharge of sequential failure of dams through flood wave analysis of sequential failure of dams and this analysis techniques to predict flood wave propagation situation in downstream regions. To this end, failure flood wave analysis were conducted for Lawn Lake Dam which is a case of sequential failure of dams among actual failure cases using DAMBRK to test the suitability of the dam failure flood wave analysis model. Based on the results, flood wave analysis of sequential failure of dams were conducted for A dam in Korea assuming a virtual extreme flood to predict flood wave propagation situations and 2-dimensional flood wave analysis were conducted for major flooding points. Then, the 1, 2-dimensional flood wave analysis were compared and analyzed. The results showed goodness-of-fit values exceeding 90% and thus the accuracy of the 1-dimensional sequential failure of dams simulation could be identified. The results of this study are considered to be able to contribute to the provision of basic data for the establishment of disaster prevention measures for rivers related to sequential failure of dams.