• Water for future
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• v.51 no.4
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• pp.6-12
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• 2018

• Water for future
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• v.54 no.7
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• pp.53-60
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• 2021

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.685-693
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• 2017

This study aims to effectively respond to urban local rainstorms by classifying the risk against flood damage for each use district. The risk classification is based on sensitivity analysis of the socio-economic damage caused by local rainstorms in Changwon city, Korea by a Fuzzy model using data, such as the districts that provide institutional bases for land use, land prices, which estimate the property values, and floor area ratios, which measures the density and areas of flood damage. The analysis result indicated that flood damage in five districts of Changwon (Masan happo-gu, Masan Hoewon-gu, Sungsan-gu, Euichang-gu, and Jinhae-gu) is highest in the order of commercial areas, residential areas, industrial areas, and forests, which was attributed to high land price and floor area ratio of commercial areas. On the other hand, specific analysis in Masan Hoewon-gu and Sungsan-gu was different from the previous result, indicating that the risk against flood damage may vary according to the districts depending on their local conditions. The analysis from this study can be applied to future urban planning and be used as a guideline to estimate the potential flood damage. Overall, this study is meaningful in that it proposes an effective management of land use as a new resolution to mitigate of urban flood damage within a broader perspective of climate change and urbanization.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.379-379
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• 2018

기후변화와 지구온난화로 인하여 전 세계적으로 폭우발생 빈도 및 강도가 증가하고 있다. 특히 유역 차원에서 도시화와 산업 개발로 인한 불투수면적 증가는 내수침수 증가로 이어지고 있다. 불투수면적이 높고 인구와 건물이 밀집되어있는 도시유역에서의 내수침수는 막대한 재산피해와 인명피해를 야기한다. 도시유역의 불투수층에 내린 강우는 지표면을 따라 흐르다가 대부분 우수관으로 유입되어 유역에서 배출된다. 그러므로 도시 우수관의 설계빈도를 결정하고 설계홍수량을 결정하는 일은 도시 홍수 저감을 위한 구조적인 대책 중 가장 우선적으로 고려되어야 하고, 또 가장 중요한 대책이기도 하다. 본 연구에서는 과거 홍수피해가 빈번히 발생했던 도시유역들 중 유역면적과 우수관망의 구조가 다른 7개의 도시를 선정하여 다양한 강우사상에 따른 유출해석을 실시하였다. 서울과 부산 기상관측소에서 관측된 1975년부터 2015년까지의 강우자료에 대한 EPA-SWMM 모형에서의 유출해석 결과 첨두강우량의 변화에 따른 첨두유출량의 변화를 선형회귀모형으로 분석하였다. 회귀모형의 결정계수와 95% 신뢰구간, 변동계수를 비교하였고, 수계밀도개념을 적용하여 첨두유출량의 변화를 해석한 결과, 우수관망이 조밀하게 건설되어 배수밀도가 높을수록 증가된 첨두강우량에 따라 함께 증가하는 첨두유출량의 예측이 상대적으로 정확하게 가능함을 확인하였다. 우수관의 구조적인 특성에 따른 유출 응답 속도를 고려하여 우수관을 설계한다면, 보다 효율적인 우수관 설계가 가능할 것으로 판단된다.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.1-10
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• 2018

Recently, localized heavy rainfall has led to increasing flood damage in urban areas such as Gangnam, Seoul ('12), Busan ('13), Ulsan ('16) Incheon and Busan ('17) etc. Urban flooding occurs relatively rapidly compared to flood damage in river basin, and property damage including damage to houses, cars and shopping centers is more serious than facility damage to structures such as levees and small bridges. In Korea, heavy rain warnings are currently announced using the criteria set by KMA (Korea Meteorological Administration). However, these criteria do not reflect regional characteristics and are not suitable to urban flood. So in this study, estimated the flooding limit rainfall amount based on the damage records for Seoul and Ulsan. And for regions that can not estimate the flooding limit rainfall since there is no damage records, we estimated the flooding limit rainfall using a Neuro-Fuzzy model with runoff characteristics. Based on the estimated flooding limit rainfall, the urban flood warning criteria was set. and applied to the actual flood event. As a result of comparing the estimated flooding limit rainfall with the actual flooding limit rainfall, the error of 1.8~20.4% occurred. And evacuation time was analyzed from a minimum of 28 minutes to a maximum of 70 minutes. Therefore, it can be used as a warning criteria in the urban flood.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.81-88
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• 2018

The rainfall-runoff model made of sewer networks in the urban area is vast and complex, making it unsuitable for real-time urban flood forecasting. Therefore, the rainfall-runoff model is constructed and simplified using the sewer network of Daerim baisn. The network simplification process was composed of 5 steps based on cumulative drainage area and all parameters of SWMM were calculated using weighted area. Also, in order to estimate the optimal simplification range of the sewage network, runoff and flood analysis was carried out by 5 simplification ranges. As a result, the number of nodes, conduits and the simulation time were constantly reduced to 50~90% according to the simplification ranges. The runoff results of simplified models show the same result before the simplification. In the 2D flood analysis, as the simplification range increases by cumulative drainage area, the number of overflow nodes significantly decreased and the positions were changed, but similar flooding pattern was appeared. However, in the case of more than 6 ha cumulative drainage area, some inundation areas could not be occurred because of deleted nodes from upstream. As a result of comparing flood area and flood depth, it was analyzed that the flood result based on simplification range of 1 ha cumulative drainage area is most similar to the analysis result before simplification. It is expected that this study can be used as reliable data suitable for real-time urban flood forecasting by simplifying sewer network considering SWMM parameters.

• Journal of the Korean association of regional geographers
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• v.12 no.1
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• pp.172-178
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• 2006

There has been tremendous increase of disaster related damages since 1990's. Especially flood occurred in summer season highly populated area has led to demolish a lot of facilities and buildings within a short time period. This is to figure out the way to predict the vulnerable flood inundation area by past records of inundation and and geographic information available. The comparative study on 1998 and 1999 flood inundation area in Munsan and Gokneung river shows that 5 degree of slope and 10 m elevation level are dividing index to draw the vulnerable area. This study is to suggest the relatively easy method to predict flood vulnerable area and to apply the results to prepare for protecting the facilities and the people with other thematic geographic database.

• Journal of KIISE
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• v.44 no.6
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• pp.607-612
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• 2017

This paper presents an attempt to apply Deep Learning technology to solve the problem of forecasting floods in urban areas. We employ Recurrent Neural Networks (RNNs), which are suitable for analyzing time series data, to learn observed data of river water and to predict the water level. To test the model, we use water observation data of a station in the Trinity river, Texas, the U.S., with data from 2013 to 2015 for training and data in 2016 for testing. Input of the neural networks is a 16-record-length sequence of 15-minute-interval time-series data, and output is the predicted value of the water level at the next 30 minutes and 60 minutes. In the experiment, we compare three Deep Learning models including standard RNN, RNN trained with Back Propagation Through Time (RNN-BPTT), and Long Short-Term Memory (LSTM). The prediction quality of LSTM can obtain Nash Efficiency exceeding 0.98, while the standard RNN and RNN-BPTT also provide very high accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.257-266
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• 2021

Urban areas can often suffer flood damage because of the more frequent catastrophic rainfall events from climate change. Flood mitigation measures consist of (1) structural and (2) non-structural measures. In this study, the proposed method focused on operating an urban drainage system among non-structural measures. The combined inland-river operation technique estimates the inflow of pump stations based on the water level obtained from a preselected monitoring point, and the pump station expels the stored rainwater to the riverside based on those estimates. In this study, the proposed method was applied to the Mokgam drainage watershed, where catastrophic rainfall events occurred (i.e., 2010- and 2011-years), and severe flood damage was recorded in Seoul. Using the proposed method, the efficiency of flood reduction from the two rainfall events was reduced by 34.9 % and 54.4 %, respectively, compared to the current operation method. Thus, the proposed method can minimize the flood damage in the Mokgam drainage watershed by reserving the additional storage space of a reservoir. In addition, flooding from catastrophic rainfall can be prevented, and citizens' lives and property in urban areas can be protected.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.276-276
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• 2021

최근 댐과 같은 수공구조물의 건설로 대규모 홍수피해는 급격히 줄어들었지만, 돌발홍수(flash flood)로 인한 저지대 침수 등의 도시홍수 발생빈도가 급증하고 있다. 2020년에는 최장의 장마가 관측되었으며, 전국적으로 홍수로 인한 침수피해가 발생하였다. 홍수에 선제적으로 대응하기 위해서 신뢰성 있는 홍수예·경보가 필요하며, 이를 위해서는 신속하고 정확성있는 강우예측이 선행되어야 한다. 이에 본 연구에서는 초단기 강우예측을 목적으로 둔 레이더 기반의 강우앙상블 예측모형을 개발하였다. 라그랑지안 지속성(Lagrangian persistence)을 기반으로 개발하였으며, 강우장의 이동 패턴은 이류특성을 활용해 추정하였다. 즉, 강우장의 예측정확도를 향상시키기 위해 공간적 규모별 캐스캐이드(cascade) 방법으로 분리해 이동 경로를 추정하였다. 예측시간에 따른 강우량은 각 캐스캐이드에 자기회귀모형을 적용하였다. 레이더 강우량은 2016-2020년 사이에 발생한 강우사상에 대한 환경부 홍수통제소에서 제공한 레이더 합성장을 이용하였다. 예측강우량에 대한 평가는 RMSE, Pearson's Correlation, FSS 등 통계치를 통해 수행하였다. 본 연구에서 소개된 강우예측 모형은 초단기 홍수예측에 정확도 높은 강우 정보를 제공할 수 있으며, 이에 따라 홍수피해를 저감하는데 도움이 될 것으로 판단된다.