Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Analysis of the applicability of parameter estimation methods for a stochastic rainfall generation model

강우모의모형의 모수 추정 최적화 기법의 적합성 분석

  • 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)
  • 조현곤 (경북대학교 건설환경에너지공학부) ;
  • 이경은 (경북대학교 통계학과) ;
  • 김광섭 (경북대학교 건설환경에너지공학부)
  • Received : 2017.10.30
  • Accepted : 2017.11.21
  • Published : 2017.11.30
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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.

강우현상을 구조적으로 모형화한 확률적 강우모의모형의 활용성이 증대되는 상황에서 확률적 강우모의모형의 모수에 대한 정확한 추정은 매우 중요하다. 본 연구에서는 확률적 강우모의모형 (Neyman-Scott rectangular pulse model, NSRPM)의 모수를 DFP (Davidon-Fletcher-Powell), GA (genetic algorithm), Nelder-Mead, DE (differential evolution) 기법으로 추정하고 추정된 모수의 적합성을 분석하고 지역특성에 적합한 모수 추정 기법을 제시하였다. 낙동강 유역의 20개 강우 관측 지점을 대상으로 1973년-2017년 기간 동안의 여름철 1시간 강수자료 이용하여 산정된 모형 모수를 분석한 결과, 전반적으로 DE, Nelder-Mead기법이 가장 좋은 결과를 보였으며 DFP, GA기법은 상대적으로 낮은 적합도를 보였다.

Keywords

Acknowledgement

Supported by : 국토교통과학기술진흥원

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