한국수자원학회논문집 (Journal of Korea Water Resources Association)

한국수자원학회 (Korea Water Resources Association)
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26 GCM 결과를 이용한 미래 홍수피해액 예측

Flood damage cost projection in Korea using 26 GCM outputs

  • 김묘정 (경북대학교 건설환경에너지공학부) ;
  • 김광섭 (경북대학교 건설환경에너지공학부)
  • Kim, Myojeong (School of Architecture, Civil, Environmental and Energy Engineering, Kyungpook National University) ;
  • Kim, Gwangseob (School of Architecture, Civil, Environmental and Energy Engineering, Kyungpook National University)
  • 투고 : 2018.07.31
  • 심사 : 2018.11.12
  • 발행 : 2018.11.30
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초록

본 연구는 우리나라 113개 중권역에 대한 기후변화에 따른 미래 홍수 피해액의 예측을 위하여 26개 GCM 모형에서 생산한 강우자료와 1시간 최대 강수량, 10분 최대 강수량, 1일 강수량이 80 mm 초과한 일수, 일 최대 강수량, 연강수량, 유역고도, 시가화율, 인구 밀도, 자산 밀도, 도로와 같은 사회 간접 시설, 하천개수율, 하수도 보급률, 배수펌프시설, 유수지용량 및 과거 홍수 피해액 자료를 활용하였다. 구축된 자료에 대하여 구속 다중선형회귀 모형(Constrained Multiple Linear Regression Model)을 적용하여 홍수 피해액과 여타 입력자료 사이의 상관관계를 구축하고 RCP 4.5와 8.5에 대한 26개 GCM 모형 산정자료를 활용하여 미래 홍수 피해액을 예측하였다. 홍수피해에 주된 요인이 되는 연강수량, 극치 강우량 등 강우관련 요소들이 전반적으로 증가하며 이로 인하여 과거 홍수로 인한 피해액이 광범위하게 증가할 것으로 판단되고 특히 동해안 및 남강댐 유역에 미래의 홍수피해액이 높게 예측되는 경향을 보인다.

This study aims to predict the future flood damage cost of 113 middle range watersheds using 26 GCM outputs, hourly maximum rainfall, 10-min maximum rainfall, number of days of 80 mm/day, daily rainfall maximum, annual rainfall amount, DEM, urbanization ratio, population density, asset density, road improvement ratio, river improvement ratio, drainage system improvement ratio, pumping capacity, detention basin capacity and previous flood damage costs. A constrained multiple linear regression model was used to construct the relationships between the flood damage cost and other variables. Future flood damage costs were estimated for different RCP scenarios such as 4.5 and 8.5. Results demonstrated that rainfall related factors such as annual rainfall amount, rainfall extremes etc. widely increase. It causes nationwide future flood damage cost increase. Especially the flood damage cost for Eastern part watersheds of Kangwondo and Namgang dam area may mainly increase.

키워드

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Fig. 1. Average Flood Risk Index According to FVI, PSR, and DPSIR Methods (2000-2015) (Kim and Kim, 2018)

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Fig. 2. Comparison between Flood Damage Cost Observation and Estimates Using CMLR Model (2000-2015)

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Fig. 3. Average of the Hydrological Characteristics for Different Target Periods and RCP Scenarios

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Fig. 4. Average of the Flood Damage Cost for Different Target Periods and RCP Scenarios

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Fig. 5. Standard Deviation of the Flood Damage Cost for Different Target Periods and RCP Scenarios

Table 1. List of input data

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Table 2. List of used GCMs

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Table 3. Correlation Coefficient by Flood Damage Cost According to FVI, PSR, and DPSIR Methods

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Table 4. Test Statistics of the Flood Damage Cost Estimates by the CMLR Model

SJOHCI_2018_v51nspc_1149_t0004.png 이미지

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