• Journal of Korea Water Resources Association
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• v.40 no.4
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• pp.313-324
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• 2007

An irregular cell-based numerical model was developed to analyze underground space flooding. In this model, the flow characteristics in underground space were computed by link-node system. Also, the model can simulate the underground flood flow related to the influence of stairs and wall-structures. Empirical discharge formula were introduced to analyze weir-type flow for shopping mall, and channel-type flow for subway railroad respectively. The simulated results matched in reasonable range compared with the observed depth. The dual-drainage inundation analysis model and the underground space flood analysis model were integrated using visual basic application of ArcGIS system. The developed model can help the decision support system of flood control authority for redesigning and constructing flood prevention structures and making the potential inundation zone, and establishing flood-mitigation measures.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.5
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• pp.647-654
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• 2005

Recently, the economic losses caused by inundation are increasing due to the urbanization and industrialization, i.e., intensive land utilization and concentration of population and properties. It is regarded that the role of the storm sewer systems in urban areas becomes more important as one of the effective countermeasures for reducing the inundation losses. In this study, the effects of rainfall design frequency enhancement on the construction cost of the storm sewer systems were analyzed by increasing the design frequency from the present design frequency of the sewer systems, which is 5~10 years, to 15 years, 20 years and 30 years. The change rate functions of the design discharge and construction cost based on the various design frequencies were derived by regression analysis. According to the analysis, change the rate of design discharge at 15, 20, 30 years rainfall design frequencies were increased by 10%, 17.1%, and 27.2%, respectively, when compared to that at 10 year frequency. Furthermore, it was found that by increasing the design frequency from 10 years to 15 years, 20 years and 30 years, the construction costs were increased by 5.0%, 8.0% and 12.4%, respectively. Finally, their reliabilities need to be tested by applying the rate functions to the real storm sewer districts.

• Journal of Korea Water Resources Association
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• v.57 no.6
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• pp.371-383
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• 2024

The quantification methods and definitions of resilience vary and are studied across many fields. However, this diversity can lead to gaps in interpretation regarding the meaning and indicators of resilience, potentially having a negative impact on resilience assessments. Therefore, uniform standards for defining and quantifying resilience are essential. This study presented a definition of resilience and socio-structural evaluation methods of resilience through network analysis. Furthermore, through analyzing various definitions of resilience, the definition of resilience in the context of urban flooding was presented. Distinguishing between static and dynamic resilience, an evaluation method based on common attributes was proposed. Lastly, the economic effects of introducing resilience were analyzed using an inundation trace map. Future research on the secondary effects through standardized resilience assessments is expected to be widely utilized in decision-making stages within urban flood policies.

• Journal of Korea Water Resources Association
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• v.48 no.2
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• pp.127-136
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• 2015

In general, XP-SWMM regards manholes as nodes, so it can not consider local head loss in surcharged manhole depending on shape and size of the manhole. That might be a reason why XP-SWMM underestimates inundated-area compared with reality. Therefore, it is necessary to study how we put the local head loss in surcharged manhole in order to simulate storm drain system with XP-SWMM. In this study, average head loss coefficients at circular and square manhole were estimated as 0.61 and 0.68 respectively through hydraulic experiments with various discharges. The estimated average head loss coefficients were put into XP-SWMM as inflow and outflow energy loss of nodes to simulate inundation area of Gunja basin. Simulated results show that not only overflow discharge amount but inundated-area increased considering the head loss coefficients. Also, inundation area with considering head loss coefficients was matched as much as 58% on real inundation area. That was more than simulated results without considering head loss coefficients as much as 18 %. Considering energy loss in surcharged manholes increases an accuracy of simulation. Therefore, the averaged head loss coefficients of this study could be used to simulate storm drain system. It was expected that the study results will be utilized as basic data for establishing the identification of the inundation risk area.

• Journal of Environmental Impact Assessment
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• v.23 no.1
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• pp.39-50
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• 2014

In recent years, the frequency and scale of the natural disasters are growing rapidly due to the global climate change. In case of the urban flooding, high-density of population and infrastructure has caused the more intensive damages. In this study, we analyzed the spatial characteristics of urban flooding damage factors using GWR(Geographically Weighted Regression) for effective disaster prevention and then, classified the causes of the flood damage by spatial characteristics. The damage factors applied consists of natural variables such as the poor drainage area, the distance from the river, elevation and slope, and anthropogenic variables such as the impervious surface area, urbanized area, and infrastructure area, which are selected by literature review. This study carried out the comparative analysis between OLS(Ordinary Least Square) and GWR model for identifying spatial non-stationarity and spatial autocorrelation, and in the results, GWR model has higher explanation power than OLS model. As a result, it appears that there are some differences between each of the flood damage areas depending on the variables. We conclude that the establishment of disaster prevention plan for urban flooding area should reflect the spatial characteristics of the damaged areas. This study provides an improved understandings of the causes of urban flood damages, which can be diverse according to their own spatial characteristics.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.121-129
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• 2020

The increase of impervious surface and development along the river due to urbanization not only causes an increase in the number of associated flood risk factors but also exacerbates flood damage, leading to difficulties in flood management. Flood control measures should be prioritized based on various geographical information in urban areas. In this study, a probabilistic flood hazard assessment was applied to flood-prone areas near an urban river. Flood hazard maps were alternatively considered and used to describe the expected inundation areas for a given set of predictors such as elevation, slope, runoff curve number, and distance to river. This study proposes a Bayesian logistic regression-based flood risk model that aims to provide a probabilistic risk metric such as population-at-risk (PAR). Finally, the logistic regression model demonstrates the probabilistic flood hazard maps for the entire area.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.2
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• pp.262-274
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• 2013

Heavy rain and heavy snow as representative extreme weather are recently an issue in urban area. The paper aims at modeling the scenarios of evacuation that minimizes economic loss of the designated urban area with improving travel efficiency by providing road closure information facing an extremely heavy rainfall. The paper develops a model by using a NetLogo toolkit applied to the study area of Seocho-dong, Seocho-gu, Seoul. The model conducts a simulation of travel time under different scenarios of information provision. The simulation results show that it is efficient to provide the information of road closure to 20~40% of the drivers under the scenario of humid road or rainfall less than 20mm, whereas to 40~60% of the drivers under the scenario of heavy rainfall more than 20mm.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.188-188
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• 2022

기후변화로 인해 전 세계적으로 홍수로 인한 피해 발생 빈도와 규모가 증가하고 있다. 인구 및 사회기반시설이 밀집되어 있는 도시에서 침수가 발생할 경우 피해 규모가 막대하여 사전에 침수를 예측하고 원인을 분석하여 예방하려는 노력이 중요하다. 본 연구에서는 고해상도 물리 기반 도시 침수 모형인 H12 모형을 이용하여 과거 침수 사상을 재현하고 발생 원인을 분석하였다. 대전광역시 서구 A 아파트 인근의 도시 유역에서는 2020년 7월 30일 새벽 발생한 집중호우로 차량 78대와 아파트 2개 동이 침수되고, 사망 1명, 이재민 56명의 피해가 발생한 바 있다. 고해상도 도시침수 모의를 통해 재해 발생 원인을 분석한 결과, 좁고 긴 유역의 형상과 유역 하류에 위치한 침수 발생 지역의 낮은 지형이 복합적으로 작용하고, 폭우로 인해 상류로부터 급속히 발생한 유출이 배수가 취약한 하류 저지대에 저류되며 발생한 내수침수 재해로 분석되었다. 또한, 침수 재해 발생 이후 설치된 침수방어벽의 홍수 방어 효과를 고해상도 모의를 통해 분석하였다. 침수방어벽 지점에 고해상도 지표면 입력자료를 수정하여 모의한 결과, 침수방어벽 설치 후 침수 지역 수심이 낮아진 것을 확인하여 침수 저감 효과를 평가하였다. 본 연구에서는 초고해상도 물리기반 모형을 이용하여 정량적으로 침수 원인 분석이 가능함을 확인하였으며, 추후 침수지역의 배수구용량 산정 등 침수 대안 수립에 활용할 수 있을 것으로 예상된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.363-369
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• 2006

A simple and an improved methods for the economic analysis of the flood control project has been in previous studies in Korea. In 2004, the Multi-Dimensional Flood Damage Analysis (MD-FDA) was developed and now it is widely used for the economic analysis of flood control project. However, the MD-FDA was developed for general damage assessment and analysis without consideration of specific regional characteristics such as urban and rural areas. To compensate the MD-FDA for the application in urban area, a part of damage estimation components is modified and a component for the flood damage estimation is suggested. The component we suggest is for the consideration of the capability of stormwater pump stations in the study area. When flood is occurred in the urban area, the damage potential is larger than the rural area because of the concentration of human lives and properties. So, many stormwater pump stations are located in the urban area and the inundation depth is estimated by considering the capabilities of pump stations. We also compensate the damage components such as the damages of industrial area, and public facilities for the flood damage estimation of the urban area. The results by the compensated MD-FDA for the urban area application with those by original MD-FDA are compared. As a result the B/C ratio showed 6.75 and 5.51 respectively for the modified and original MD-FDA. This difference might be largely affected by the damage rate of the public facilities.