DOI QR코드

DOI QR Code

포아송 클러스터 강우생성 모형의 홍수 모의 적용성 평가

The Application of the Poisson Cluster Rainfall Generation Model to the Flood Analysis

  • 김동균 (홍익대학교 건설도시공학부) ;
  • 신지예 (한양대학교 대학원 건설환경공학과) ;
  • 이승오 (홍익대학교 건설도시공학부) ;
  • 김태웅 (한양대학교 공학대학 건설환경플랜트공학과)
  • Kim, Dongkyun (Department of Civil and Urban Engineering, Hongik University) ;
  • Shin, Ji Yae (Department of Civil and Environmental Engineering, Hanyang University) ;
  • Lee, Seung-Oh (Department of Civil and Urban Engineering, Hongik University) ;
  • Kim, Tae-Woong (Department of Civil and Environmental Engineering, Hanyang University)
  • 투고 : 2012.11.07
  • 심사 : 2013.01.28
  • 발행 : 2013.05.31

초록

본 연구는 우리나라 전역에 대하여 제작된 Modified Bartlett-Lewis Rectangular Pulse (MBLRP) 강우생성 모형의 모수 지도의 적용성을 홍수 재현의 관점에서 평가하였다. MBLRP 모형을 통해 생성된 가상 강우시계열을 사용하여 산정된 확률강우량은 관측치를 사용하여 산정된 확률강우량 보다 약5%에서 40%정도 작았고, 확률강우량의 재현기간이 클수록 과소산정의 정도가 크게 나타났다. 가상의 도시 유역에 MBLRP 모형을 적용하여 산정한 확률홍수량은 관측치를 사용하여 산정한 확률홍수량 보다 약20%에서 45%정도 작게 나타났고, 확률홍수량의 재현기간이 클수록, 그리고 유역의 불투수성이 작을수록 과소산정의 정도가 크게 나타났다.

The applicability of the parameter map of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) model for the Korean Peninsula was assessed from the perspective of flood prediction. The design rainfalls estimated from the MBLRP model were smaller than those from observed values by 5% to 40%, and the degree of underestimation of design rainfall increases with the increase of the recurrence interval of the design rainfall. The design floods at a virtual watershed estimated using the simulated rainfall time series based on MBLRP model were also smaller than those derived from the observed rainfall time series by 20% to 45%. The degree of underestimation of design flood increases with the increase of the recurrence interval of the design flood.

키워드

참고문헌

  1. Bathurst, J.C., and Bovolo, C.I. (2004). Development of Guidelines for Sustainable Land Management in the Agri and Cobres Target Basins, Deliverable 28 of the EU Funded MEDACTION Project, p. 37. Available from: http://www.ncl.ac.uk/medaction.
  2. Bathurst, J.C., Moretti, G., El-Hames, A., Moaven-Hashemi, A., and Burton, A. (2005). "Scenario modeling of basinscale, shallow landslide sediment yield, Valsassina, Italian Southern Alps." Natural Hazards and Earth System Sciences, Vol. 5, pp. 189-202. https://doi.org/10.5194/nhess-5-189-2005
  3. Brath, A., Montanari, A., and Moretti, G. (2006). "Assessing the effect on flood frequency of land use change via hydrological simulation(with uncertainty)." Journal of Hydrology, Vol. 324, Issues 1-4, pp. 141-153. https://doi.org/10.1016/j.jhydrol.2005.10.001
  4. Burton, A., Kilsby, C.G., Fowler, H.J., Cowpertwait, P.S.P., and O'Connell, P.E. (2008). "RainSim: a spatialtemporal stochastic rainfall modelling system." Environmental Modelling & Software, Vol. 23, Issue 12, pp. 1356-1369. https://doi.org/10.1016/j.envsoft.2008.04.003
  5. Cho, H., Kim, D., Olivera, F., and Guikema, S. (2011). "Enhanced speciation in particle swarm optimization for multi-modal problems." European Journal of Operations Research, Vol. 213, Issue 1, pp. 15-23. https://doi.org/10.1016/j.ejor.2011.02.026
  6. Cowpertwait, P.S.P., O'Connell, P.E., Metcalfe, A.V., and Mawdsley, J.A. (1996). "Stochastic point process modelling of rainfall. II. Regionalisation and disaggregation." Journal of Hydrology, Vol. 175, pp. 47-65. https://doi.org/10.1016/S0022-1694(96)80005-9
  7. Dawson, R., Hall, J., Speight, L., Djordjevic, S., Savic, D., and Leandro, J. (2006). "Flood risk analysis to support integrated urban drainage." Proceedings of the Fourth CIWEM Annual Conference on Emerging Environmental Issues and Future Challenges, 12-14 September 2006, Newcastle upon Tyne. Aqua Enviro, pp. 10.
  8. Fowler, H.J., Kilsby, C.G., O'Connell, P.E., and Burton, A. (2005). "A weather-type conditioned multi-site stochastic rainfall model for the generation of scenarios of climatic variability and change." Journal ofHydrology, Vol. 308, Issues 1-4, pp. 50-66. https://doi.org/10.1016/j.jhydrol.2004.10.021
  9. Kilsby, C.G., Burton, A., Birkinshaw, S.J., Hashemi, A.M., and O'Connell, P.E. (2000). "Extreme rainfall and flood frequency distribution modelling for present and future climates." Proceedings of the British Hydrological Society Seventh National Hydrology Symposium, pp. 3.51-3.56.
  10. Kim, D., Lee, S., Choi, M., and Jung, Y. (2012). "Regionalization of the modified Bartlett-Lewis Rectangular Pulse rainfall model across Korean Peninsular." Submitted to Stochastic and Environmental Research and Risk Analysis.
  11. Korea Meteorological Administration (2012). "http://www.kma.go.kr/weather/observation/past_cal.jsp
  12. Moretti, G., and Montanari, A. (2004). "Estimation of the peak river flow for an ungauged mountain creek using a distributed rainfall-runoff model." In: A. Brath, A. Montanari, E. Toth (eds.), Hydrological Risk: Recent Advances in Peak River FlowModelling, Prediction and Real-Time Forecasting-Assessment of the Impacts of Land-Use and Climate Changes. BIOS, Cosenza, Italy, pp. 113-128.
  13. Nolan, B.T., Dubus, I.G., Surdyk, N., Fowler, H.J., Burton, A., Hollis, J.M., Reichenberger, S., and Jarvis, N.J. (2008). "Identification of key climatic factors regulating the transport of pesticides in leaching and to tile drains." Pest Management Science, Vol. 64, Issue 9, pp. 933-944. https://doi.org/10.1002/ps.1587
  14. Rodriguez-Iturbe, I., Cox, D.R., and Isham, V. (1988). "A point process model for rainfall: Further developments." Proceedings of the Royal Society of London Series A-Mathematical Physical and Engineering Sciences, Vol. 417, No. 1853, pp. 283-298.

피인용 문헌

  1. Development and validation of poisson cluster stochastic rainfall generation web application across South Korea vol.49, pp.4, 2016, https://doi.org/10.3741/JKWRA.2016.49.4.335
  2. Projection of Climate Change with Uncertainties: 2. Internal Variability vol.14, pp.5, 2014, https://doi.org/10.9798/KOSHAM.2014.14.5.329
  3. Evaluation of the Applicability of the Poisson Cluster Rainfall Generation Model for Modeling Extreme Hydrological Events vol.34, pp.3, 2014, https://doi.org/10.12652/Ksce.2014.34.3.0773
  4. A hierarchical Bayesian approach to the modified Bartlett-Lewis rectangular pulse model for a joint estimation of model parameters across stations vol.544, 2017, https://doi.org/10.1016/j.jhydrol.2016.11.031
  5. Application of the Poisson Cluster Rainfall Generation Model to the Urban Flood Analysis vol.48, pp.9, 2015, https://doi.org/10.3741/JKWRA.2015.48.9.729
  6. A development of downscaling scheme for sub-daily extreme precipitation using conditional copula model vol.49, pp.10, 2016, https://doi.org/10.3741/JKWRA.2016.49.10.863
  7. A Development of Hourly Rainfall Simulation Technique Based on Bayesian MBLRP Model vol.34, pp.3, 2014, https://doi.org/10.12652/Ksce.2014.34.3.0821
  8. A development of multisite hourly rainfall simulation technique based on neyman-scott rectangular pulse model vol.49, pp.11, 2016, https://doi.org/10.3741/JKWRA.2016.49.11.913