Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
권호 표지
DOI QR코드

DOI QR Code

Research on flood risk forecast method using weather ensemble prediction system in urban region

앙상블 기상예측 자료를 활용한 도시지역의 홍수위험도 예측 방안에 관한 연구

  • Choi, Youngje (Department of Civil System Engineering, Ajou University) ;
  • Yi, Jaeeung (Department of Civil System Engineering, Ajou University)
  • 최영제 (아주대학교 건설시스템공학과) ;
  • 이재응 (아주대학교 건설시스템공학과)
  • Received : 2019.08.30
  • Accepted : 2019.10.10
  • Published : 2019.10.31
Download PDF
⟨ Previous Next ⟩

Abstract

Localized heavy storm is one of the major causes of flood damage in urban regions. According to the recent disaster statistics in South Korea, the frequency of urban flood is increasing more frequently, and the scale is also increasing. However, localized heavy storm is difficult to predict, making it difficult for local government officials to deal with floods. This study aims to construct a Flood risk matrix (FRM) using ensemble weather prediction data and to assess its applicability as a means of reducing damage by securing time for such urban flood response. The FRM is a two-dimensional matrix of potential impacts (X-axis) representing flood risk and likelihood (Y-axis) representing the occurrence probability of dangerous weather events. To this end, a regional FRM was constructed using historical flood damage records and probability precipitation data for basic municipality in Busan and Daegu. Applicability of the regional FRMs was assessed by applying the LENS data of the Korea Meteorological Administration on past heavy rain events. As a result, it was analyzed that the flood risk could be predicted up to 3 days ago, and it would be helpful to reduce the damage by securing the flood response time in practice.

여름철 집중호우는 도시지역의 홍수피해를 발생시키는 주요한 원인 중 하나이다. 우리나라의 최근 재해통계에 따르면 도시홍수의 발생빈도는 점점 잦아지고 있으며, 그 규모 또한 커지고 있다. 하지만 국지성 집중호우는 예측이 어려워 실제 홍수 대응을 담당하는 지자체 공무원들의 업무에 어려움이 있다. 따라서 본 연구에서는 이러한 도시홍수 대응에 시간적 여유 확보를 통한 피해 저감을 위해 앙상블 기상예측 자료를 활용한 홍수위험 매트릭스를 구축하고, 그 적용성을 판단하고자 하였다. 홍수위험 매트릭스는 홍수위험도의 정도를 나타내는 잠재적 영향(X축), 위험 기상현상이 발생할 확률인 발생가능성(Y축)으로 구성된 2차원 매트릭스로 확률예보에 기반한 홍수위험 예측 방안이다. 이를 위해 부산 및 대구광역시 내 기초지자체 각각 1곳을 대상으로 과거 홍수피해기록과 확률강우량 자료를 활용하여 지역별 홍수위험 매트릭스를 구축하고, 과거 호우사상에 대해 기상청의 LENS 자료를 적용하여 그 적용성을 판단하였다. 그 결과 최대 3일전 홍수위험에 대한 예측이 가능한 것으로 분석되었으며 실제 활용 시 홍수 대응시간을 확보하여 피해 저감에 도움이 되리라 판단된다.

Keywords

References

  1. Anderson, M. G., and Burt, T. P. (1985). Hydrological forecasting. John Wiley & Sons, New York. pp. 32-63.
  2. Cheung, K. K. (2001). "A review of ensemble forecasting techniques with a focus on tropical cyclone forecasting." Meteorological Applications, Vol. 8, No. 3, pp. 315-332. https://doi.org/10.1017/S1350482701003073
  3. Choi, C. W., Jung, D. J., Cho, J. W., Kang, H. S., Bae, C. Y., and Kim, M. J. (2017). Development of advanced technique for urban flood alert criteria. NDMI-PR-2017-01-02, National Disaster Management Institute, Ulsan, South Korea.
  4. Chung, K. Y. (2016). "Vision and direction of impact forecasting." Meteorological Technology & Policy, Vol. 9, No. 1, pp. 6-22.
  5. Crichton, D. (1999). The risk triangle. Natural Disaster Management, Ingleton, J.,(ed.), Tudor Rose London.
  6. Henonin, J., Russo, B., Mark, O., and Gourbesville, P. (2013). "Real-time urban flood forecasting and modelling-a state of the art." Journal of Hydroinformatics, Vol. 15, No. 3, pp. 717-736. https://doi.org/10.2166/hydro.2013.132
  7. Keum, H. J., Kim, H. I., and Han, K. Y. (2018). "Real-time forecast of rainfall impact of urban inundation." Journal of the Korean Association of Geographic Information Studies, Vol. 21, No. 3, pp. 76-92. https://doi.org/10.11108/KAGIS.2018.21.3.076
  8. Korea Meteorological Association (KMA) (2018). 2018 Year book on meteorological. Korea Meteorological Association, Seoul, South Korea.
  9. Lee, B. J. (2017). "Analysis on inundation characteristics for flood impact forecasting in gangnam drainage basin." Atmosphere, Korean Meteorological Society, Vol. 27, No. 2, pp. 189-197. https://doi.org/10.14191/Atmos.2017.27.2.189
  10. Lee, H. J., Ryu, S. H., Won, S. H., Jo, E. J., Kim, S. W., and Joe, G. H. (2016). "A study on model of heavy rain risk prediction using influencing factors of flood damage." Journal of Korean Society of Hazard Mitigation, Vol. 16, No. 3, pp. 39-45. https://doi.org/10.9798/KOSHAM.2016.16.3.39
  11. Lee, S. W., Park, J. H., and Kim, D. J. (2015). "Limited area ensemble prediction system(LENS) in KMA toward early warning system for high impact weather." Proceeding of the Autumn Meeting of KMS, pp. 237-238.
  12. Ministry of the Interior and Safety (MOIS) (2000-2016). 2000-2016 Disaster annual report.
  13. Noymanee, J., Nikitin, N. O., and Kalyuzhnaya, A. V. (2017). "Urban pluvial flood forecasting using open data with machine learning techniques in Pattani basin." Procedia computer science, Vol. 119, pp. 288-297. https://doi.org/10.1016/j.procs.2017.11.187
  14. Park, S. S., and Kang, B. S. (2014). "Differentiating scheme for the storm warning criteria considering the regional disaster prevention capacity." Journal of Korean Society of Hazard Mitigation, Vol. 14, No. 5, pp. 67-76. https://doi.org/10.9798/KOSHAM.2014.14.5.67
  15. Pilling, C. (2016). "New developments at the Flood Forecasting Centre: operations and flood risk guidance." WIT Transactions on The Built Environment, Vol. 165, pp. 237-248. https://doi.org/10.2495/UW160211
  16. Son, M. S., Park, J. Y., and Kim, H. S. (2013). "Urban environmental risk-evaluating flooding risk indices of Seoul." Seoul Studies, Vol. 14, No. 4, pp. 127-140.
  17. Song, Y. S., Lim, C. H., Joo, J. G., and Park, M. J. (2016). "A study on heavy rain forecast evaluation and improvement method." Journal of Korean Society of Hazard Mitigation, Vol. 16, No. 2, pp. 113-121. https://doi.org/10.9798/KOSHAM.2016.16.2.113
  18. World Meteorological Organization (WMO) (2011). Manual on flood forecasting and warning. WMO-No. 1072, World Meteorological Organization, Geneva, Switzerland.
  19. World Meteorological Organization (WMO) (2015). WMO guidelines on multi-hazard impact-based forecast and warning Services. WMO-No. 1150, World Meteorological Organization, Geneva, Switzerland.