• Title/Summary/Keyword: 도시침수 저감

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Applicability of SURR Model for Geum-River Basin (금강 유역에 대한 SURR 모형의 적용성 평가)

  • Lim, Ye Jin;Heo, Jae-Yeong;Ngoc, Tien Duong;Bae, Deg-Hyo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.361-361
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    • 2022
  • 최근 기후변화의 영향으로 국지성 집중호우에 의한 홍수 피해가 빈번히 발생하고 있으며, 이로 인한 인명 및 재산 피해가 증가하고 있다. 2020년의 경우, 최장 기간 장마로 인해 금강유역을 비롯한 전국에서 산사태, 제방 붕괴, 침수 등 많은 피해가 발생하였다. 이러한 홍수피해 저감을 위해서는 신뢰도 높은 홍수량 예측이 요구된다. 특히, 토양수분과 같이 시간에 따른 유역 수문 정보를 모의 과정에서 고려하는 것이 매우 중요하다. 아울러, 유역 전반에 대한 토양수분 정보는 실시간으로 획득하는 것이 어려워 이를 고려할 수 있는 강우-유출모형을 활용하는 것이 바람직하다. 이러한 수문모형으로 SURR(Sejong University Rainfall Runoff) 모형이 있으며 다양한 적용 및 평가를 통해 모형 활용성에 대한 증진이 요구되는 실정이다. 본 연구에서는 저류함수 기반의 시단위 연속형 강우-유출모형(SURR 모형)을 활용한 강우-유출 모의를 수행하여 홍수 피해가 컸던 금강유역을 대상으로 모형의 적용성을 평가하고자 한다. 평가기간은 2006~2020년으로써 유량관측 지점별 매개변수 검·보정을 수행하였다. 관측 및 모의 유량에 대한 도시적 및 통계적(CC, RMSE, NSE) 평가를 수행하여 유출 모의에 대한 정확도를 평가하였다. 평가결과, 관측 및 모의 유량 간의 거동이 유사한 것으로 나타났으며 첨두유량 및 시간이 비교적 잘 일치하는 것으로 나타나 대상유역의 신뢰도 높은 유출량을 모의하는데 적합한 것으로 확인되었다. 본 연구 결과는 향후 AI 기법과 연계한 돌발홍수 예측 연구에 활용하여 정확도 높은 유역 홍수량 예측 및 선행시간 확보에 도움이 될 것으로 기대된다.

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The study of heavy rain warning in Gangwon State using threshold rainfall (침수유발 강우량을 이용한 강원특별자치도 호우특보 기준에 관한 연구)

  • Lee, Hyeonjia;Kang, Donghob;Lee, Iksangc;Kim, Byungsikd
    • Journal of Korea Water Resources Association
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    • v.56 no.11
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    • pp.751-764
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    • 2023
  • Gangwon State is centered on the Taebaek Mountains with very different climate characteristics depending on the region, and localized heavy rainfall is a frequent occurrence. Heavy rain disasters have a short duration and high spatial and temporal variability, causing many casualties and property damage. In the last 10 years (2012~2021), the number of heavy rain disasters in Gangwon State was 28, with an average cost of 45.6 billion won. To reduce heavy rain disasters, it is necessary to establish a disaster management plan at the local level. In particular, the current criteria for heavy rain warnings are uniform and do not consider local characteristics. Therefore, this study aims to propose a heavy rainfall warning criteria that considers the threshold rainfall for the advisory areas located in Gangwon State. As a result of analyzing the representative value of threshold rainfall by advisory area, the Mean value was similar to the criteria for issuing a heavy rain warning, and it was selected as the criteria for a heavy rain warning in this study. The rainfall events of Typhoon Mitag in 2019, Typhoons Maysak and Haishen in 2020, and Typhoon Khanun in 2023 were applied as rainfall events to review the criteria for heavy rainfall warnings, as a result of Hit Rate accuracy verification, this study reflects the actual warning well with 72% in Gangneung Plain and 98% in Wonju. The criteria for heavy rain warnings in this study are the same as the crisis warning stages (Attention, Caution, Alert, and Danger), which are considered to be possible for preemptive rain disaster response. The results of this study are expected to complement the uniform decision-making system for responding to heavy rain disasters in the future and can be used as a basis for heavy rain warnings that consider disaster risk by region.

An Experimental Study for Estimation of Head Loss Coefficients at Surcharged Circular Manhole (과부하 원형맨홀에서의 손실계수 산정을 위한 실험적 연구)

  • Kim, Jung-Soo;Song, Ju-Il;Jang, Suk-Jin;Yoon, Sei-Eui
    • Journal of Korea Water Resources Association
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    • v.41 no.3
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    • pp.305-314
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    • 2008
  • Urban sewer systems are designed to operate in open-channel flow regime and energy loss at circular manholes are usually not significant. However, the energy loss at manholes, often exceeding the friction loss of pipes under surcharge flow, is considered as one of the major causes of inundation in urban area. Therefore, it is necessary to analyze the head loss associated with manholes, especially in surcharge flow. Hydraulic experimental apparatus which can be changed the invert type(CASE A, B, C) and step height(CASE I, II, III) was installed for this study. The range of the experimental discharges were from $1.0{\ell}/sec$ to $5.6\;{\ell}/sec$. As the manhole diameter ratio($D_m/D_{in}$) increases, head loss coefficient increases due to strong horizontal swirl motion. Head loss coefficient was maximum because of strong oscillation of water surface when the range of manhole depth ratios($h_m/D_{in}$) were from 1.0 to 1.5. The average head loss coefficients for CASE A, B, and C were 0.45, 0.37, and 0.30, respectively. Accordingly, U-invert is most effective for energy loss reduction at circular manhole. This head loss coefficients could be available to design the urban sewer system with surcharge flow.

Flood vulnerability analysis in Seoul, Korea (한국 도심지에서의 홍수취약성 분석)

  • Hwang, Nanhee;Park, Heeseong;Chung, Gunhui
    • Journal of Korea Water Resources Association
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    • v.52 no.10
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    • pp.729-742
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    • 2019
  • Natural disasters such as floods has been increased in many parts of the world, also Korea is no exception. The biggest part of natural damage in South Korea was caused by the flooding during the rainy season in every summer. The existing flood vulnerability analysis cannot explain the reality because of the repeated changes in topography. Therefore, it is necessary to calculate a new flood vulnerability index in accordance with the changed terrain and socio-economic environment. The priority of the investment for the flood prevention and mitigation has to be determined using the new flood vulnerability index. Total 25 urban districts in Seoul were selected as the study area. Flood vulnerability factors were developed using Pressure-State-Response (PSR) structures. The Pressure Index (PI) includes nine factors such as population density and number of vehicles, and so on. Four factors such as damage of public facilities, etc. for the Status Index (SI) were selected. Finally, seven factors for Response Index (RI) were selected such as the number of evacuation facilities and financial independence, etc. The weights of factors were calculated using AHP method and Fuzzy AHP to implement the uncertainties in the decision making process. As a result, PI and RI were changed, but the ranks in PI and RI were not be changed significantly. However, SI were changed significanlty in terms of the weight method. Flood vulnerability index using Fuzzy AHP shows less vulnerability index in Southern part of Han river. This would be the reason that cost of flood mitigation, number of government workers and Financial self-reliance are high.

A Study on the Determination of Optimal Location and Size for Underground Sluiceway Design (지하방수로 설계를 위한 적정 위치선정 및 규모 결정에 관한 연구)

  • Lee, Jong-Tae;Lim, Taek-Sun;Hur, Sung-Chul;Park, Sang-Sik
    • Journal of the Korean Society of Hazard Mitigation
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    • v.8 no.5
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    • pp.137-145
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    • 2008
  • In this study, to reduce the flood damage caused by flood discharge exceeding project flood, the primary technology was applied to determining the optimal location and size for underground sluiceway. The Jungrang Stream was selected for this study because the stream was overflowed and the embankment section of the stream was destroyed owing to localized torrential rainfall in 1998 and 2001. Considering 200-year frequency storm, the inlets of the underground discharge channel were located at Seoul City limits, the confluence of Danghyun Stream, Wolgye 1-gyo, and the confluence of Mukdong Stream. The outlets were located at the estuary of Jungrang Stream and rightbank of Banpo Bridge in Han River. The transverse discharge according to the variation of overflow depth at the inlet of underground discharge channel was estimated and the effect of inundation reduction was analyzed. To examine the appropriate scale of the underground discharge channel, the 8 operation methods for the management of outlet discharge were compared considering four rules (only storage, the constant discharge rate, the constant discharge volume, and the mixture of the constant discharge rate and discharge volume). As a result, the effect of inundation reduction was most significantly improved when the inlet was located at the confluence of Danghyun Stream. The appropriate size of underground sluiceway for 200-year frequency storm was studied, and as a result, the appropriate diameters of the underground discharge channel were 12 m in case of only storage(Rule D), 9m in 50% of discharge(Rule E), 8 m in constant discharge volume(Rule F), and 7 m in mixture method(Rule G). This investigation process can be applied to design the underground discharge channel when the inundation damage is significant in coastal area due to embankment overflow. The underground discharge channel in Jungrang Stream can also be used as an underground road to link Seoul City to Uijeongbu City during dry season.

Development of 1ST-Model for 1 hour-heavy rain damage scale prediction based on AI models (1시간 호우피해 규모 예측을 위한 AI 기반의 1ST-모형 개발)

  • Lee, Joonhak;Lee, Haneul;Kang, Narae;Hwang, Seokhwan;Kim, Hung Soo;Kim, Soojun
    • Journal of Korea Water Resources Association
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    • v.56 no.5
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    • pp.311-323
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    • 2023
  • In order to reduce disaster damage by localized heavy rains, floods, and urban inundation, it is important to know in advance whether natural disasters occur. Currently, heavy rain watch and heavy rain warning by the criteria of the Korea Meteorological Administration are being issued in Korea. However, since this one criterion is applied to the whole country, we can not clearly recognize heavy rain damage for a specific region in advance. Therefore, in this paper, we tried to reset the current criteria for a special weather report which considers the regional characteristics and to predict the damage caused by rainfall after 1 hour. The study area was selected as Gyeonggi-province, where has more frequent heavy rain damage than other regions. Then, the rainfall inducing disaster or hazard-triggering rainfall was set by utilizing hourly rainfall and heavy rain damage data, considering the local characteristics. The heavy rain damage prediction model was developed by a decision tree model and a random forest model, which are machine learning technique and by rainfall inducing disaster and rainfall data. In addition, long short-term memory and deep neural network models were used for predicting rainfall after 1 hour. The predicted rainfall by a developed prediction model was applied to the trained classification model and we predicted whether the rain damage after 1 hour will be occurred or not and we called this as 1ST-Model. The 1ST-Model can be used for preventing and preparing heavy rain disaster and it is judged to be of great contribution in reducing damage caused by heavy rain.