Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
권호 표지
DOI QR코드

DOI QR Code

A development of multisite hourly rainfall simulation technique based on neyman-scott rectangular pulse model

Neyman-Scott Rectangular Pulse 모형 기반의 다지점 강수모의 기법 개발

  • Moon, Jangwon (Department of Civil Engineering, University of Seoul) ;
  • Kim, Janggyeong (Department of Civil Engineering, Chonbuk National University) ;
  • Moon, Youngil (Department of Civil Engineering, University of Seoul) ;
  • Kwon, Hyunhan (Department of Civil Engineering, Chonbuk National University)
  • 문장원 (서울시립대학교 토목공학과) ;
  • 김장경 (전북대학교 토목공학과) ;
  • 문영일 (서울시립대학교 토목공학과) ;
  • 권현한 (전북대학교 토목공학과)
  • Received : 2016.09.04
  • Accepted : 2016.09.20
  • Published : 2016.11.30
Download PDF
⟨ Previous Next ⟩

Abstract

A long-term precipitation record is typically required for establishing the reliable water resources plan in the watershed. However, the observations in the hourly precipitation data are not always consistent and there are missing values within the time series. This study aims to develop a hourly rainfall simulator for extending rainfall data, based on the well-known Neyman-Scott Rectangular Pulse Model (NSRPM). Moreover, this study further suggests a multisite hourly rainfall simulator to better reproduce areal rainfalls for the watershed. The proposed model was validated with a network of five weather stations in the Uee-stream watershed in Seoul. The proposed model appeared a reasonable result in terms of reproducing most of the statistics (i.e. mean, variance and lag-1 autocovariance) of the rainfall time series at various aggregation levels and the spatial coherence over the weather stations.

유역의 신뢰성 있는 수자원계획을 수립하기 위해서는 장기간의 강수자료가 필수적으로 요구된다. 그러나 시간강수시계열의 경우 결측치가 상대적으로 많으며, 연속적인 시계열을 확보하는데 어려움이 있다. 이러한 점에서 본 연구에서는 대표적인 시간강수모의기법인 Neyman-Scott Rectangular Pulse Model (NSRPM) 기반의 강수모의기법을 활용하여, 모의기반의 장기강수자료를 생산할 수 있는 기법을 개발하고자 한다. 이와 더불어, 신뢰성 있는 면적강수량을 추정하기 위한 방안으로 유역 내 여러 지점의 강수량을 동시에 모의할 수 있는 다지점 시간강수모의기법을 개발하였다. 개발된 모형은 서울 우이천 유역 강수지점에 적용하여 모형의 적합성을 평가하였다. 모형 적용결과 다양한 지속시간에 대해서 강수량의 효과적인 모의(평균, 분산, 1차 자기상관계수)가 가능하였으며, 지점간의 공간성도 효과적으로 복원 가능하였다.

Keywords

References

  1. Ailliot, P., Thompson, C., and Thomson, P. (2009). "Space-time modelling of precipitation by using a hidden markov model and censored gaussian distributions." J R Stat Soc C-Appl, Vol. 58, pp. 405-426. https://doi.org/10.1111/j.1467-9876.2008.00654.x
  2. Apipattanavis, S., Podesta, G., Rajagopalan, B., and Katz, R. W. (2007). "A semiparametric multivariate and multisite weather generator." Water Resour Res, Vol. 43, No. 11.
  3. Bardossy, A., and Pegram, G. G. S. (2009). "Copula based multisite model for daily precipitation simulation." Hydrol Earth Syst Sc., Vol. 13, No. 12, pp. 2299-2314. https://doi.org/10.5194/hess-13-2299-2009
  4. Boughton, W., and Droop, O. (2003). "Continuous simulation for design flood estimation-a review." Environ. Modell. Softw., Vol. 18, No. 4, pp. 309-318, doi:10.1016/S1364-8152(03)00004-5.
  5. Brocca, L., Liersch, S., and Melone, F. (2013). "Application of a model-based rainfall-runoff database as efficient tool for flood risk management." Hydrology and Earth System Sciences, Vol. 17, No. 8, pp. 3159-3169. https://doi.org/10.5194/hess-17-3159-2013
  6. Charles, S. P., Bates, B. C., and Hughes, J. P. (1999), "A spatiotemporal model for downscaling precipitation occurrence and amounts." J Geophys Res-Atmos, Vol. 104, No. D24, pp. 31657-31669. https://doi.org/10.1029/1999JD900119
  7. Cho, H., Kim, D., Olivera, F., and Guikema, S. D. (2011). "Enhanced speciation in particle swarm optimization for multi-modal problems." Eur. J. Oper. Res., Vol. 213, No. 1, pp. 15-23, doi:10.1016/j.ejor.2011.02.026.
  8. Cowpertwait, P. S. P., O'Connell, P. E., Metcalfe, A. V., and Mawdsley, J. A. (1996). "Stochastic point process modelling of rainfall I. Single-site fitting and validation." J. Hydrol., Vol. 175, No. 1, pp. 17-46, doi:10.1016/S0022-1694(96)80004-7.
  9. Entekhabi, D., Rodriguez-Iturbe, I., and Eagleson, P. S. (1989). "Probabilistic representation of the temporal rainfall process by a modified neyman-scott rectangular pulses model: Parameter estimation and validation." Water Resour. Res., Vol. 25, No. 2, pp. 295-302, doi:10.1029/WR025i002p00295.
  10. 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." J. Hydrol., Vol. 308, No. 1-4, pp. 50-66, doi:10.1016/j.jhydrol.2004.10.021.
  11. Hill, R. R., Jr (1996). "Multivariate sampling with explicit correlation induction for simulation and optimization studies." Vol. 1, No. AFIT-96-003D. AIR FORCE INST OF TECH WRIGHTPATTERSONAFB OH.
  12. Hughes, J. P., Guttorp, P., and Charles, S. P. (1999). "A nonhomogeneous hidden Markov model for precipitation occurrence." J. R. Stat. Soc. Ser. C Appl. Stat., Vol. 48, No. 1, pp. 15-30, doi:10.1111/1467-9876.00136.
  13. Khalil, A. F., Kwon, H. H., Lall, U., and Kaheil, Y. H. (2010). "Predictive downscaling based on non-homogeneous hidden Markov models." Hydrolog Sci J, Vol. 55, No. 3, pp. 333-350. https://doi.org/10.1080/02626661003780342
  14. Kim, D., and Olivera, F. (2012). "Relative importance of the different rainfall statistics in the calibration of stochastic rainfall generation models." J. Hydrol. Eng., Vol. 17, No. 3, pp. 368-376, doi:10.1061/(ASCE)HE.1943-5584.0000453.
  15. Kim, D., Olivera, F., and Cho, H. (2013a). "Effect of the inter-annual variability of rainfall statistics on stochastically generated rainfall time series: Part 1. Impact on peak and extreme rainfall values." Stoch. Environ. Res. Risk Assess., Vol. 27, No. 7, pp. 1601-1610, doi:10.1007/s00477-013-0696-z.
  16. Kim, D., Olivera, F., Cho, H., and Lee, S. O. (2013b). "Effect of the inter-annual variability of rainfall statistics on stochastically generated rainfall time series: Part 2. Impact on watershed response variables." Stoch. Environ. Res. Risk Assess., Vol. 27, No. 7, pp. 1611-1619, doi:10.1007/s00477-013-0697-y.
  17. Kim, D., Cho, H., Onof, C., and Choi, M. (2016b). "Let-It-Rain: A web application for stochastic point rainfall generation at ungaged basins and its applicability in runoff and flood modeling." Stoch. Environ. Res. Risk Assess., pp. 1-21, doi:10.1007/s00477-016-1234-6.
  18. Kim, D., Kwon, H.-H., Lee, S.-O., and Kim, S. (2016a). "Regionalization of the modified bartlett-lewis rectangular pulse stochastic rainfall model across the korean peninsula." Journal of Hydro-environment Research, Vol. 11, pp. 123-137, doi:10.1016/j.jher.2014.10.004.
  19. Kim, D., Shin, J. Y., Lee, S.-O., and Kim, T.-W. (2013c). "The application of the poisson cluster rainfall generation model to the flood analysis." Journal of Korea Water Resources Association, Vol. 46, No. 5, pp. 439-447, doi:10.3741/JKWRA.2013.46.5.439.
  20. Kim, J. G., Kwon, H. H., and Kim, D. K. (2014a). "A development of hourly rainfall simulation technique based on bayesian MBLRP model." Journal of The Korean Society of Civil Engineers, Vol. 34, No. 3, pp. 821-831, doi:10.12652/Ksce.2014.34.3.0821.
  21. Kim, K.-W., and Yoo, C.-S. (2008). "A selection of the point rainfall process model considered on temporal clustering characteristics." Journal of Korea Water Resources Association, Vol. 41, No. 7, pp. 747-759, doi:10.3741/JKWRA.2008.41.7.747.
  22. Kim, T.-J., Kwon, H.-H., Lee, D.-R., and Yoon, S.-K. (2014b). "Development of stochastic downscaling method for rainfall data using GCM." Journal of Korea Water Resources Association, Vol. 47, No. 9, pp. 825-838, doi:10.3741/JKWRA.2014.47.9.825.
  23. Kwon, H. H., Kim, T. J., Hwang, S.-H., and Kim, T.-W. (2013). "Development of daily rainfall simulation model based on homogeneous hidden markov Chain." Journal of The Korean Society of Civil Engineers, Vol. 33, No. 5, 1861-1870, doi:10.12652/Ksce.2013.33.5.1861.
  24. Kwon, H. H., Lall, U., and Obeysekera, J. (2009). "Simulation of daily rainfall scenarios with interannual and multidecadal climate cycles for South Florida." Stoch Env Res Risk A, Vol. 23, No. 7, pp. 879-896. https://doi.org/10.1007/s00477-008-0270-2
  25. Kyoung, M.-S., Sivakumar, B., Kim, H.-S., and Kim, B.-S. (2008). "Chaotic disaggregation of daily rainfall time series." Journal of Korea Water Resources Association, Vol. 41, No. 9, pp. 959-967, doi:10.3741/JKWRA.2008.41.9.959.
  26. Lagarias, J. C., Reeds, J. A., Wright, M. H., and Wright, P. E. (1998). "Convergence properties of the nelder-mead simplex method in low dimensions." SIAM J. Optim., Vol. 9, No. 1, pp. 112-147, doi:10.1137/S1052623496303470.
  27. Li, C., Singh, V. P., and Mishra, A. K. (2013), A bivariate mixed distribution with a heavy-tailed component and its application to single-site daily rainfall simulation, Water Resour Res, Vol. 49, No. 2, pp. 767-789. https://doi.org/10.1002/wrcr.20063
  28. Onof, C., Chandler, R. E., Kakou, A., Northrop, P., Wheater, H. S., and Isham, V. (2000). "Rainfall modelling using Poissoncluster processes: A review of developments." Stoch. Environ. Res. Risk Assess., Vol. 14, No. 6, pp. 384-411, doi:10.1007/s004770000043.
  29. Owen, A. B. (1994), "Controlling correlations in Latin hypercube samples." Journal of the American Statistical Association, Vol. 89, No. 428, pp. 1517-1522. https://doi.org/10.1080/01621459.1994.10476891
  30. Park, H., Yang, J., Han, J., and Kim, D. (2015). "Application of the poisson cluster rainfall generation model to the urban flood analysis." Journal of Korea Water Resources Association, Vol. 48, No. 9, pp. 729-741, doi:10.3741/JKWRA.2015.48.9.729.
  31. Rajagopalan, B., and Lall, U. (1999). "A k-nearest-neighhor simulator for daily precipitation and other weather variables." Water Resour Res, Vol. 35, No. 10, pp. 3089-3101. https://doi.org/10.1029/1999WR900028
  32. Rodriguez-Iturbe, I., Power, B. F., and Valdes, J. (1987b). "Rectangular pulses point process models for rainfall: Analysis of empirical data." Journal of Geophysical Research: Atmospheres (1984-2012), Vol. 92, Issue D8, pp. 9645-9656. https://doi.org/10.1029/JD092iD08p09645
  33. Rodriguez-Iturbe, I., Cox, D., and Isham, V. (1987a). "Some models for rainfall based on stochastic point processes." Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences, Vol. 410, Issue 1839, pp. 269-288. https://doi.org/10.1098/rspa.1987.0039
  34. Rodriguez-Iturbe, I., Cox, D., and Isham, V. (1988). "A point process model for rainfall: further developments." Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences, Vol. 417, Issue 1853, pp. 283-298. https://doi.org/10.1098/rspa.1988.0061
  35. So, B.-J., Kwon, H.-H., Kim, D., and Lee, S. O. (2015). "Modeling of daily rainfall sequence and extremes based on a semiparametric Pareto tail approach at multiple locations." J. Hydrol., Vol. 529, No. 3, pp. 1442-1450, doi:10.1016/j.jhydrol.2015.08.037.
  36. Vanhaute, W. J., Vandenberghe, S., Scheerlinck, K., Baets, B. D., and Verhoest, N. (2012). "Calibration of the modified Bartlett-Lewis model using global optimization techniques and alternative objective functions." Hydrol. Earth Syst. Sci., Vol. 16, No. 3, pp. 873-891. https://doi.org/10.5194/hess-16-873-2012
  37. Velghe, T., Troch, P. A., De Troch, F. P., and Van de Velde, J. (1994). "Evaluation of cluster-based rectangular pulses point process models for rainfall." Water Resour. Res., Vol. 30, No. 10, pp. 2847-2857, doi:10.1029/94WR01496.
  38. Verhoest, N., Troch, P. A., and De Troch, F. P. (1997). "On the applicability of Bartlett-Lewis rectangular pulses models in the modeling of design storms at a point." J. Hydrol., Vol. 202, No. 1-4, pp. 108-120, doi:10.1016/S0022-1694(97)00060-7.
  39. Wheater, H. S., Isham, V. S., Chandler, R. E., Onof, C. J., and Stewart, E. J. (2006). "Improved methods for national spatial-temporal rainfall and evaporation modelling for BSM." R&D Technical Report, pp. 400.
  40. Zheng, X., and Katz, R. W. (2008a). "Simulation of spatial dependence in daily rainfall using multisite generators." Water Resour. Res., Vol. 44, No. 9, W09403, doi:10.1029/2007WR006399.
  41. Zheng, X., and Katz, R. W. (2008b). "Mixture model of generalized chain-dependent processes and its application to simulation of interannual variability of daily rainfall." J. Hydrol., Vol. 349, No. 1-2, pp. 191-199, doi:10.1016/j.jhydrol.2007.10.061.
  42. Zheng, X., Renwick, J., and Clark, A. (2010). "Simulation of multisite precipitation using an extended chain-dependent process." Water Resour. Res., Vol. 46, W01504, doi:10.1029/2008WR007526.