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한국 도심지에서의 홍수취약성 분석

Flood vulnerability analysis in Seoul, Korea

  • 황난희 (호서대학교 토목공학과) ;
  • 박희성 (한국건설기술연구원 국토보전연구본부) ;
  • 정건희 (호서대학교 건축토목환경공학부 토목공학전공)
  • Hwang, Nanhee (Department of Civil Engineering, Hoseo University) ;
  • Park, Heeseong (Department of Land, Water and Environment Research, Korea Institute of Civil engineering and building Technology (KICT)) ;
  • Chung, Gunhui (Department of Civil Engineering, Hoseo University)
  • 투고 : 2019.05.21
  • 심사 : 2019.09.27
  • 발행 : 2019.10.31

초록

국내의 자연재해피해 중 가장 큰 부분을 대부분은 매년 여름철에 발생하고 있는 태풍과 장마로 인한 침수피해이므로, 도시 홍수에 대한 관심은 꾸준히 증가하고 있다. 반복되는 피해 저감을 위해 다양한 방법으로 홍수취약성을 분석하지만, 반복되는 도시(재)개발로 인해 지형 및 사회경제적인 요인들이 바뀌고 있어, 기존에 실시했던 홍수취약성 분석결과가 현실적으로 반영이 되기 힘든 상태이다. 이에 홍수피해 예방을 위해 변형된 지형과 환경에 맞춰 새로운 홍수취약성 분석을 실시하여 지역의 투자 우선순위를 파악할 필요가 있다. 본 연구에서는 우리나라 중 가장 도시화가 된 서울시 25개 구를 대상지역으로 선정하였으며, 홍수취약성 인자들을 Pressure-State-Response (PSR) 구조로 구분하였다. 압력지수(PI)는 인구밀도, 차량 수 등 9개의 인자를, 상태지수(SI)는 공공시설 피해액 등 4개의 인자를 선정하였으며, 대책지수(RI)는 대피시설 수, 재정자립도 등 7개의 인자를 선택하여 홍수취약성지수를 계산하였다. 각 인자들의 가중치를 계산하기 위해 AHP 방법과 Fuzzy이론을 결합한 Fuzzy AHP 방법을 적용하였다. 그 결과, 세부지수인 압력지수나 대책지수는 가중치 결정방법에 따라 숫자가 변하기는 하지만, 순위 변화는 없었으며, 상태지수는 값 뿐만 아니라 순위에도 다소 변화가 있었다. 또한 세부지수들을 결합하여 계산한 홍수취약성지수는 Fuzzy AHP 방법으로 계산하였을 경우, 강남 지역의 취약성이 눈에 띄게 감소하였다. 이는 강남지역의 홍수피해복구금액이나 재정자립도가 높고, 다른 지자체와 차이가 크기 때문에 Fuzzy 수를 이용하여 불확실성을 고려할 경우 취약성이 낮아진 것으로 분석된다.

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.

키워드

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