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http://dx.doi.org/10.7465/jkdi.2017.28.6.1447

Analysis of the applicability of parameter estimation methods for a stochastic rainfall generation model  

Cho, Hyungon (School of Architectural, Civil, Environment, and Energy Engineering, Kyungpook National University)
Lee, Kyeong Eun (Department of Statistics, Kyungpook National University)
Kim, Gwangseob (School of Architectural, Civil, Environment, and Energy Engineering, Kyungpook National University)
Publication Information
Journal of the Korean Data and Information Science Society / v.28, no.6, 2017 , pp. 1447-1456 More about this Journal
Abstract
Accurate inference of parameters of a stochastic rainfall generation model is essential to improve the applicability of the rainfall generation model which modeled the rainfall process and the structure of rainfall events. In this study, the model parameters of a stochastic rainfall generation model, NSRPM (Neyman-Scott rectangular pulse model), were estimated using DFP (Davidon-Fletcher-Powell), GA (genetic algorithm), Nelder-Mead, and DE (differential evolution) methods. Summer season hourly rainfall data of 20 rainfall observation sites within the Nakdong river basin from 1973 to 2017 were used to estimate parameters and the regional applicability of inference methods were analyzed. Overall results demonstrated that DE and Nelder-Mead methods generate better results than that of DFP and GA methods.
Keywords
Davidon-Fletcher-Powell; differential evolution; genetic algorithm; Nelder-Mead; parameter estimation; stochastic rainfall generation model;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 Cowpertwait, P. S. P. (1991). Further developments of the Neyman-Scott clustered point process for modeling rainfall. Water Resources Research, 27, 1431-1438.   DOI
2 Cowperwait, 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. Journal of Hydrology, 175, 17-46.   DOI
3 Entekhabi, D., Rodriguez-Iturbe, I. and Eagleson, P. S. (1989). Probabilistic representation of the temporal rainfall by a modified Neyman-Scott rectangular pulse model: Parameter estimation and validation. Water Resources Research, 25, 295-302.   DOI
4 Islam, S., Entekhabi, D., Bras, R. L. and Rodriguez-Iturbe, I. (1990). Parameter estimation and sensitivity analysis for the modified Bartlett-Lewis rectangular pulses model of rainfall. Journal of Geophysical Research, 95, 2093-2100.   DOI
5 Jeong, C.-S. (2009). Study of direct parameter estimation for Neyman-Scott ractangular pulse model. Journal of Korea Water Resources Association, 42, 1017-1028.   DOI
6 Kim, G. S., Cho, H. G. and Yi, J. E. (2012). Parameter estimation of the Neyman-Scott rectangular pulse model using a differential evolution method. Journal of Korean Society of Hazard Mitigation, 12, 187-194.   DOI
7 Rodriguez-Iturbe, I. (1986). Scale of fluctuation of rainfall models. Water Resources Research, 22, 15-37.   DOI
8 Lee, J.-Y. and Goh, J. Y. (2009) Selection of the principal genotype with genetic algorithm. Journal of the Korean Data & Information Science Society, 20, 639-647.
9 Rodriguez-Iturbe, I., Cox, D.R. and Isham, V. (1987). Some models for rainfall based on stochastic point processes. Proceedings of the Royal Society of London A, 410, 269-288.   DOI
10 Lee, J. and Kim, Y. (2016) A spatial analysis of Neyman-Scott rectangular pulses model using an approximate likelihood function. Journal of the Korean Data & Information Science Society, 27, 1119-1131.   DOI
11 Velghe, T., Troch, P. A., De Troch, F. P. and Van de Velde, J. (1994). Evaluation of cluster-based rectangular pulse point process models for rainfall. Water Resource Research, 30, 2847-2857.   DOI
12 Kum, J.-H., Ahn, J.-H., Kim, J.-H. and Yoon, Y.-N. (2001). Parameter estimation of a point rainfall model, Neyman-Scott rectangular pulses model. Proceedings of Korea Water Resources Association Conference, 206-211.