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http://dx.doi.org/10.3741/JKWRA.2018.51.1.1

Development and application of urban flood alert criteria considering damage records and runoff characteristics  

Cho, Jeawoong (National Disaster Management Research Institute)
Bae, Changyeon (National Disaster Management Research Institute)
Kang, Hoseon (National Disaster Management Research Institute)
Publication Information
Journal of Korea Water Resources Association / v.51, no.1, 2018 , pp. 1-10 More about this Journal
Abstract
Recently, localized heavy rainfall has led to increasing flood damage in urban areas such as Gangnam, Seoul ('12), Busan ('13), Ulsan ('16) Incheon and Busan ('17) etc. Urban flooding occurs relatively rapidly compared to flood damage in river basin, and property damage including damage to houses, cars and shopping centers is more serious than facility damage to structures such as levees and small bridges. In Korea, heavy rain warnings are currently announced using the criteria set by KMA (Korea Meteorological Administration). However, these criteria do not reflect regional characteristics and are not suitable to urban flood. So in this study, estimated the flooding limit rainfall amount based on the damage records for Seoul and Ulsan. And for regions that can not estimate the flooding limit rainfall since there is no damage records, we estimated the flooding limit rainfall using a Neuro-Fuzzy model with runoff characteristics. Based on the estimated flooding limit rainfall, the urban flood warning criteria was set. and applied to the actual flood event. As a result of comparing the estimated flooding limit rainfall with the actual flooding limit rainfall, the error of 1.8~20.4% occurred. And evacuation time was analyzed from a minimum of 28 minutes to a maximum of 70 minutes. Therefore, it can be used as a warning criteria in the urban flood.
Keywords
Urban flooding; Warning criteria; Limit rainfall; Neuro-Fuzzy model;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 Jun, H. D., Lee, J. H., and Park, M. J. (2013). "Flood forecasting methodology for mid and small rivers using a coupling of upper-and down stream water level stations." Magazine of Kosham, Vol. 12, No. 4, pp. 49-57.
2 Kim, J., and Kasabov, N. (1999). "HYFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems." Neural Networks, Vol. 12, No. 9, pp. 1301-1319.   DOI
3 Korea Meteorological Agency. www.kma.go.kr.
4 Lin, C. T., and Lee, C. S .G. (1996). Neural fuzzy systems: a neurofuzzy synergism to intellingent systems. Prentice-Hall, Upper Saddle River, N.J.
5 Ministry of Environment and National Institute of Environmental Research, Korean Climate Change Assessment Report (2014).
6 National Disaster Management Research Institute (2015). Establishment of foundation for regional urban flood response system.
7 Song, Y. H., and Lee, J. H. (2016). "Analysis of flood prediction and warning alert standard for urban mid and small stream." Proceedings of the Korea Contents Association Conference, Vol. 2016, No. 5, pp. 463-464.
8 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." Journal of Korean Society of Hazard Mitigation, Vol. 14, No. 2, pp. 289-298.   DOI
9 Brown, M., and Harris, C. (1994). Neuro-Fuzzy adaptive modelling and control. Prentice-Hall, Upper Saddle River, N.J.
10 Cred Crunch 45 (2016). 2016 preliminary data: Human impact of natural dsasters. Centre for Research on the Epidemiology of Disasters (CRED).
11 Japan Meteorological Agency. www.jma.go.jp.