Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
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Generation of runoff ensemble members using the shot noise process based rainfall-runoff model

Shot Noise Process 기반 강우-유출 모형을 이용한 유출 앙상블 멤버 생성

  • Kang, Minseok (School of Civil, Environmental and Architectural Engineering, Korea University) ;
  • Cho, Eunsaem (School of Civil, Environmental and Architectural Engineering, Korea University) ;
  • Yoo, Chulsang (School of Civil, Environmental and Architectural Engineering, Korea University)
  • 강민석 (고려대학교 공과대학 건축사회환경공학부) ;
  • 조은샘 (고려대학교 공과대학 건축사회환경공학부) ;
  • 유철상 (고려대학교 공과대학 건축사회환경공학부)
  • Received : 2019.08.12
  • Accepted : 2019.08.28
  • Published : 2019.09.30
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Abstract

This study proposes a method to generate runoff ensemble members using a rainfall-runoff model based on the shot noise process (hereafter the rainfall-runoff model). The proposed method was applied to generate runoff ensemble members for three drainage basins of Daerim 2, Guro 1 and the Jungdong, whose results were then compared with the observed. The parameters of the rainfall-runoff model were estimated using the empirical formulas like the Kerby, Kraven II and Russel, also the concept of modified rational formula. Gamma and exponential distributions were used to generate random numbers of the parameters of the rainfall-runoff model. Especially, the gamma distribution is found to be useful to generate various random numbers depending on the pre-assigned relationship between mean and standard deviation. Comparison between the generated runoff ensemble members and the observed shows that those runoff ensemble members generated using the gamma distribution with its standard deviation twice of the mean properly cover the observed runoff.

본 연구에서는 shot noise process 기반 강우-유출 모형(이하 강우-유출 모형)을 이용하여 유출 앙상블 멤버를 생성하는 방법을 제안하였다. 아울러 제안된 방법을 적용하여 대림 2, 구로 1, 중동 빗물펌프장 등 3개 배수유역에 대한 유출 앙상블 멤버를 생성하고, 이를 관측 유출량과 비교해 보았다. 강우-유출 모형의 매개변수는 Kerby 공식, Kraven II 공식, Russel 공식 및 수정합리식의 개념을 이용하여 추정하였다. 강우-유출 모형 매개변수의 난수 발생을 위해서는 감마분포와 지수분포를 이용하였다. 특히, 감마분포의 경우에는 평균과 표준편차의 관계를 어떻게 설정하느냐에 따라 다양한 난수 발생이 가능함을 확인하였다. 생성된 유출 앙상블과 관측 유출량과의 비교 결과, 표준편차가 평균의 두 배인 감마 분포를 이용하여 만든 유출 앙상블이 관측 유출량을 가장 적절히 포괄함을 확인하였다.

Keywords

References

  1. Bae, D., and Kim, J. (2007). "Development of Korea flash flood guidance system: (I) theory and system design." Journal of Korean Society of Civil engineering, KSCE, Vol. 27, No. 3B, pp. 237-243.
  2. Bernier, J., Morlat, G., O'Connell, P. E., O'Donnell, T., Sneyers, R., Delaporte, P. J., Elston, D., and Borgman, L. E. (1970). "Inventaire des modeles de processus stochastiques applicables a la description des debits journaliers des rivieres." Revue de l'institut International de Statistique, ISI, Vol. 38, No. 1, pp. 49-104. https://doi.org/10.2307/1402324
  3. Claps, P., and Murrone, F. (1994). "Optimal parameter estimation of conceptually-based streamflow models by time series aggregation." In Stochastic and Statistical Methods in Hydrology and Environmental Engineering, pp. 421-434.
  4. Claps, P., Giordano, A., and Laio, F. (2005). "Advances in shot noise modeling of daily streamflows." Advances in water resources, Vol. 28, No. 9, pp. 992-1000. https://doi.org/10.1016/j.advwatres.2005.03.008
  5. Cowpertwait, P. S. P., and O'Connell, P. E. (1992). "A Neyman-Scott shot noise model for the generation of daily streamflow time series." Advances in Theoretical Hydrology-A Tribute to James Dooge, pp. 75-94.
  6. Gouweleeuw, B. T., Thielen, J., Franchello, G. D., De Roo, A. P. J., and Buizza, R. (2005). "Flood forecasting using medium-range probabilistic weather prediction." Hydrology and Earth System Sciences Discussions, European Geophysical Society, Vol. 9, No. 4, pp. 365-380.
  7. Hofmann, J., and Schuttrumpf, H. (2019). "Risk-based early warning system for pluvial flash floods: approaches and foundations." Geoscience, MDPI, Vol. 9, No. 3.
  8. Hutton, J. L. (1990). "Non-negative time series models for dry river flow." Journal of Applied Probability, APT, Vol. 27, No. 1, pp. 171-182. https://doi.org/10.2307/3214604
  9. Jeong, J. H., and Yoon, Y. N. (2007). Water resources design practice. Goomibook, Seoul.
  10. Jo, D. (2014). "Application of the urban flooding forecasting by the flood nomograph." Journal of the Korean Society Hazard Mitigation, KOSHAM, Vol. 14, No. 6, pp. 421-425. https://doi.org/10.9798/KOSHAM.2014.14.6.421
  11. Kang, M., and Yoo, C. (2018). "Development of a shot noise process based rainfall-runoff model for urban flood warning system." Journal of Korea Water Resources Association, KWRA, Vol. 51, No. 1, pp. 19-33. https://doi.org/10.3741/JKWRA.2018.51.1.19
  12. Kim, H., Hwang, J., Ahn, J., and Jeong, C. (2018a). "Analysis of rate discharge change on urban catchment considering climate change." Journal of Korean Society of Civil Engineering, KSCE, Vol. 38, No. 5, pp. 645-654.
  13. Kim, H., Keum, H., and Han, K. (2018b). "Application and comparison of dynamic artificial neural networks for urban inundation analysis." Journal of Korean Society of Civil Engineering, KSCE, Vol. 38, No. 5, pp. 671-683.
  14. Kneis, D., Abon, C., Bronstert, A., and Heistermann, M. (2017). "Verification of short-term runoff forecasts for a small Philippine basin (Marikina)." Hydrological Sciences Journal, Vol. 62, No. 2, pp. 205-216. https://doi.org/10.1080/02626667.2016.1183773
  15. Komma, J., Reszler, C., Blöschl, G., and Haiden, T. (2007). "Ensemble prediction of floods? catchment non-linearity and forecast probabilities." Natural Hazards and Earth System Science, EGU, Vol. 7, No. 4, pp. 431-444. https://doi.org/10.5194/nhess-7-431-2007
  16. Konrad, C. P. (2003). Effects of urban development on floods. USGS, Reston, Virginia.
  17. Lee, H., Ryu, S., Won, S., Jo, E., Kim, S., and Joe, G. (2016). "A study on model of heavy rain risk prediction using influencing factors of flood damage." Journal of the Korean Society Hazard Mitigation, KOSHAM, Vol. 16, No. 3, pp. 39-45. https://doi.org/10.9798/KOSHAM.2016.16.3.39
  18. Lee, M., Jung, I., and Bae, D. (2011). "Korean flood vulnerability assessment on climate change." Journal of Korea Water Resources Association, KWRA, Vol. 44, No. 8, pp. 653-666. https://doi.org/10.3741/JKWRA.2011.44.8.653
  19. Lee, M., Kang, N., Kim, J., and Kim, H. S. (2018). "Estimation of optimal runoff hydrograph using radar rainfall ensemble and blending technique of rainfall-runoff models." Journal of Korea Water Resources Association, KWRA, Vol. 51, No. 3, pp. 221-233. https://doi.org/10.3741/JKWRA.2018.51.3.221
  20. Lee, S. J., Kim, J. C., Hwang, M. H., and Maeng, S. J. (2010). "Forecasting monthly runoff using ensemble streamflow prediction." Journal of the Korean Society of Agricultural Engineers, KSAE, Vol. 52, No. 1, pp. 13-18. https://doi.org/10.5389/KSAE.2010.52.1.013
  21. Ministry of Land, Transport and Maritime Affairs (MLTMA) (2009). A Study on an application of urban runoff model for urban flood forcasting. Ministry of Land, Transport and Maritime Affairs.
  22. Morlando, F., Cimorelli, L., Cozzolino, L., Mancini, G., Pianese, D., and Garofalo, F. (2016). "Shot noise modeling of daily streamflows: A hybrid spectral-and time-domain calibration approach." Water Resources Research, Vol. 52, No. 6, pp. 4730-4744. https://doi.org/10.1002/2015WR017613
  23. Murrone, F., Rossi, F., and Claps, P. (1997). "Conceptually-based shot noise modeling of streamflows at short time interval." Stochastic Hydrology and Hydraulics, Vol. 11, No. 6, pp. 483-510. https://doi.org/10.1007/BF02428430
  24. Najafi, M. R., and Moradkhani, H. (2015). "Multi-model ensemble analysis of runoff extremes for climate change impact assessments." Journal of Hydrology, Vol. 525, pp. 352-361. https://doi.org/10.1016/j.jhydrol.2015.03.045
  25. Nester, T., Komma, J., Viglione, A., and Blöschl, G. (2012). "Flood forecast errors and ensemble spread-A case study." Water Resources Research, American Geophysical Union, Vol. 48, No. 10.
  26. O'Connell, P. E., and Jones, D. A. (1979). "Some experience with the development of models for the stochastic simulation of daily flows." Inputs for Risk Analysis in Water Resources, pp. 287-314.
  27. Ponce, V. M (1989). Engineering hydrology: Principles and practices. Prentice-Hall, New Jersey.
  28. Schreider, S. Y., Smith, D. I., and Jakeman, A. J. (2000). "Climate change impacts on urban flooding." Climatic Change, Vol. 47, No. 1-2, pp. 91-115. https://doi.org/10.1023/A:1005621523177
  29. Song, Y., Song, Y., Park, M., and Lee, J. (2015). "Preliminary feasibility study on alert standard rainfall for urban mid and small rivers." Journal of the Korean Society Hazard Mitigation, KOSHAM, Vol. 15, No. 1, pp. 315-326. https://doi.org/10.9798/KOSHAM.2015.15.1.315
  30. Todorovic, P., and Woolhiser, D. A. (1987). "A shot-noise model of streamflow." In Flood Hydrology,pp. 143-163.
  31. Weiss, G. (1973). Filtered poisson processes as models for daily streamflow data. Ph. D. dissertation, Imperial College London, London, United Kingdom.
  32. Weiss, G. (1977). "Shot noise models for the generation of synthetic streamflow data." Water Resources Research, Vol. 13, No. 1, pp. 101-108. https://doi.org/10.1029/WR013i001p00101
  33. Yu, W., Choi, M., Jeong, A., and Jung, K. (2017). "Ensemble rainfall estimation and flood forecast by considering spatial prediction uncertainty of numerical weather prediction." Journal of the Korean Society of Hazard Mitigation, KOSHAM, Vol. 17, No. 5, pp. 43-55. https://doi.org/10.9798/KOSHAM.2017.17.5.43