대한토목학회논문집 (KSCE Journal of Civil and Environmental Engineering Research)

  • 제39권6호
  • /
  • Pages.713-723
  • /
  • 2019
  • /
  • 1015-6348(pISSN)
  • /
  • 2799-9629(eISSN)
대한토목학회 (Korean Society of Civil Engeneers)
권호 표지
DOI QR코드

DOI QR Code

로지스틱 회귀에 의한 도시 침수발생의 한계강우량 산정

Computation of Criterion Rainfall for Urban Flood by Logistic Regression

  • 김현일 (경북대학교 건설환경에너지공학부) ;
  • 한건연 (경북대학교 토목공학과)
  • 투고 : 2019.08.23
  • 심사 : 2019.10.21
  • 발행 : 2019.12.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

기후변화와 다양한 강우 패턴에 의하여 도시 유역 별 침수발생 기준을 산정하기에 어려움이 있다. 이에 도시 유역의 상세 지형, 배수체계 그리고 다양한 강우 시나리오를 고려하여 침수해석을 실시 및 결과를 검토할 필요가 있으며, 동일 지역에 대한 실측 강우에 따른 침수 사상을 조사할 필요가 있다. 본 연구에서는 서울시 효자 배수분구의 침수 발생에 영향을 미치는 강우 특성을 파악하기 위해 확률론적 빈도 분석과 Huff 분포를 고려한 다양한 강우 시나리오를 생성하였으며, 1차원 도시유출해석을 위한 SWMM (Storm Water Management Model)과 2차원 침수해석 모형을 이용하였다. 본 연구에서 사용된 SWMM 모형은 침수흔적도와 유전자 알고리즘을 통해 최적화 되었다. 최적화 된 1차원 모형을 2차원 침수해석과 연계하여 기존의 침수흔적도와 73.6 %의 적합도를 나타낼 수 있었다. 각 강우량에 따른 침수 발생 유무를 파악하였으며, 로지스틱 회귀 곡선을 통하여 침수발생 한계강우량을 산정할 수 있었다. 1-2차원 침수해석 결과와 2010~2018년 AWS (Automated Weather System)자료와 ASOS (Automated Synoptic Observing System)를 반영한 결과, 지속시간 1시간의 경우 침수발생 한계강우량은 72.04 mm, 2시간의 경우 146.83 mm, 3시간의 경우 203.06 mm으로 산정되었다. 산정된 한계강우량은 지속적으로 관측되는 강우 자료의 입력을 통하여 갱신될 수 있을 것으로 보인다. 본 연구에서 제시되는 방법론을 통해 도시 배수분구별 정량적 한계강우량을 제시할 수 있을 것으로 보이며, 이는 도시 유역에서 홍수 예·경보 발령을 위한 기초자료를 제공할 수 있을 것으로 판단된다.

Due to the climate change and various rainfall pattern, it is difficult to estimate a rainfall criterion which cause inundation for urban drainage districts. It is necessary to examine the result of inundation analysis by considering the detailed topography of the watershed, drainage system, and various rainfall scenarios. In this study, various rainfall scenarios were considered with the probabilistic rainfall and Huff's time distribution method in order to identify the rainfall characteristics affecting the inundation of the Hyoja drainage basin. Flood analysis was performed with SWMM and two-dimensional inundation analysis model and the parameters of SWMM were optimized with flood trace map and GA (Genetic Algorithm). By linking SWMM and two-dimensional flood analysis model, the fitness ratio between the existing flood trace and simulated inundation map turned out to be 73.6 %. The occurrence of inundation according to each rainfall scenario was identified, and the rainfall criterion could be estimated through the logistic regression method. By reflecting the results of one/two dimensional flood analysis, and AWS/ASOS data during 2010~2018, the rainfall criteria for inundation occurrence were estimated as 72.04 mm, 146.83 mm, 203.06 mm in 1, 2 and 3 hr of rainfall duration repectively. The rainfall criterion could be re-estimated through input of continuously observed rainfall data. The methodology presented in this study is expected to provide a quantitative rainfall criterion for urban drainage area, and the basic data for flood warning and evacuation plan.

키워드

참고문헌

  1. Abanco, C., Hurlimann, M., Moya, J. and Berenguer, M. (2016). "Critical rainfall conditions for the initiation of torrential flows. result from the rebaixader catchment (central pyrenees)." Journal of Hydrology, Vol. 541, pp. 218-229. https://doi.org/10.1016/j.jhydrol.2016.01.019
  2. Cho, J. H. and Lee, J. H. (2006). "Parameter optimization for runoff calibration of SWMM." Journal of Environmental Impact Assessment, Vol. 15, No. 6, pp. 435-441 (in Korean).
  3. Cho, J. W., Bae, C. Y. and Kang, H. S. (2018). "Development and application of urban flood alert criteria considering damage records and runoff characteristics." J. Korea Water Resour. Assoc., KWRA, Vol. 51, No. 1, pp. 1-10 (in Korean). https://doi.org/10.3741/JKWRA.2018.51.1.1
  4. Gardner, K. K. and Vogel, R. M. (2005). "Predicting ground water nitrate concentration from land use." Ground Water, Vol. 43, No. 3, pp. 343-352. https://doi.org/10.1111/j.1745-6584.2005.0031.x
  5. Guzzetti, F., Peruccacci, S., Rossi, M. and Stark, C. P. (2007). "Rainfall thresholds for the initiation of landslides in central and southern europe." Meteorology and Atmospheric Physics, Vol. 98, pp. 239-267. https://doi.org/10.1007/s00703-007-0262-7
  6. Huber, W. C. and Dickson, R. E. (1988). Storm water management model. user's manual ver. 4, U.S. EPA, Georgia, USA.
  7. Ji, H. S., Lee, B. J, Bae, H. D., Lee, C. K. and Jung, H. S. (2013). "Development of criterion rainfall estimation methodology in each grid for sudden flood prediction." Journal of Korean Meteorological Society, Vol. 10, pp. 248-249.
  8. Kim, Y. R. (2015). Seoul flood control policy. Seoul Policy Archive, Available at: https://seoulsolution.kr (in Korean).
  9. Korea Meteorological Agency (2019). Meteorological database. Available at: https://data.kma.go.kr (Accessed: July 4, 2019).
  10. Lee, S. H., Kang, D. H. and Kim, B. S. (2018). "A study on the method of calculating the threshold rainfall for rainfall impact forecasting." J. Korean Soc. Hazard Mitig., KSHM, Vol. 18, No. 7, pp. 93-102 (in Korean). https://doi.org/10.9798/kosham.2018.18.7.93
  11. Lim, J. T. and Kim, B. H. (2019). "Modeling for debris flow behavior on expressway using FLO-2D." J. Korean Soc. Civ. Eng., KSCE, Vol. 39, No. 2, pp. 263-272 (in Korean). https://doi.org/10.12652/KSCE.2019.39.2.0263
  12. Liong, S. Y., Chan, W. T. and Ram, S. J. (1995). "Peak flow forecasting with genetic algorithm and SWMM." Journal of Hydraulic Engineering, ASCE, Vol. 121, No. 8, pp. 613-617. https://doi.org/10.1061/(ASCE)0733-9429(1995)121:8(613)
  13. Ministry of the Interior and Safety (MOIS) (2017). Report on disaster performance goal of rainfall made climate change (in Korean).
  14. Ministry of the Interior and Safety (MOIS) (2019). Information open portal. Flood trace data. Available at: https://www.open.go.kr (Accessed: July 10, 2019).
  15. Nandi, A., Mandal, A., Wilson, M. and Smith, D. (2016). "Flood hazard mapping in Jamaica using principal component analysis and logistic regression." Environment Earth Science, Vol. 75, No. 465.
  16. Ozdemir, A. (2011). "Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey)." Journal of Hydrology, Vol. 405, No. 1-2, pp. 123-136. https://doi.org/10.1016/j.jhydrol.2011.05.015
  17. Pradhan, B. (2009). "Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing." Journal of Spatial Hydrology, Vol. 9, No. 2, pp. 1-18.
  18. Seo, K. W. and Cho, W. C. (1998). "The sensitivity analysis of parameters of urban runoff models due to variations of basin characteristics (I)." J. Korea Water Resour. Assoc., KWRA,Vol. 31, No, 3, pp. 243-252 (in Korean).
  19. Seoul Metropolitan City (2015). Comprehensive plan for storm and flood damage reduction, Korea, Vol. 1, Chapter 3, pp. 374-375 (in Korean).
  20. Shin, S. Y., Yeo, C. G., Baek, C. H. and Kim, Y. J. (2005). "Mapping inundation areas by flash flood and developing rainfall standards for evacuation in urban settings." Journal of the Korean Association of Geographic Information Studies, Vol. 8, No. 4, pp. 71-80.
  21. Son, A. L., Kim, B. H. and Han, K. Y. (2015). "A study on prediction of inundation area considering road network in urban area." J. Korean Soc. Civ. Eng., KSCE, Vol. 35, No. 2, pp. 307-318 (in Korean). https://doi.org/10.12652/Ksce.2015.35.2.0307
  22. Song, Y. H., Song, Y. S., Park, M. J. and Lee, J. H. (2014). "Flood forecasting estimation methodology of standard rainfall for urban mid and small rivers considering upper- and down-stream water levels." J. Korean Soc. Hazard Mitig., KSHM, Vol. 14, No. 2, pp. 289-298. https://doi.org/10.9798/KOSHAM.2014.14.2.289
  23. Tayfur, G. (2012). Soft computing in water resources engineering, WIT Press, Southampton, Boston.
  24. United States Environmental Protection Agency (EPA) (2010). Storm water management model user's manual version 5.0. Environmental Protection Agency, United States.