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http://dx.doi.org/10.3741/JKWRA.2019.52.10.753

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

Choi, Youngje (Department of Civil System Engineering, Ajou University)
Yi, Jaeeung (Department of Civil System Engineering, Ajou University)
Publication Information
Journal of Korea Water Resources Association / v.52, no.10, 2019 , pp. 753-761 More about this Journal
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.
Keywords
Urban flood; Flood risk; Flood risk matrix; Ensemble weather prediction;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 Chung, K. Y. (2016). "Vision and direction of impact forecasting." Meteorological Technology & Policy, Vol. 9, No. 1, pp. 6-22.
2 Crichton, D. (1999). The risk triangle. Natural Disaster Management, Ingleton, J.,(ed.), Tudor Rose London.
3 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.   DOI
4 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.   DOI
5 Korea Meteorological Association (KMA) (2018). 2018 Year book on meteorological. Korea Meteorological Association, Seoul, South Korea.
6 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.   DOI
7 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.   DOI
8 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.
9 Ministry of the Interior and Safety (MOIS) (2000-2016). 2000-2016 Disaster annual report.
10 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.   DOI
11 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.   DOI
12 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.   DOI
13 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.
14 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.   DOI
15 World Meteorological Organization (WMO) (2011). Manual on flood forecasting and warning. WMO-No. 1072, World Meteorological Organization, Geneva, Switzerland.
16 World Meteorological Organization (WMO) (2015). WMO guidelines on multi-hazard impact-based forecast and warning Services. WMO-No. 1150, World Meteorological Organization, Geneva, Switzerland.
17 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.
18 Anderson, M. G., and Burt, T. P. (1985). Hydrological forecasting. John Wiley & Sons, New York. pp. 32-63.
19 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.   DOI