Journal of The Korean Society of Agricultural Engineers (한국농공학회논문집)

The Korean Society of Agricultural Engineers (한국농공학회)
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Evaluation of Parameter Estimation Method for Design Rainfall Estimation

설계강우량 산정을 위한 매개변수 추정방법 평가

  • Kim, Kwihoon (Department of Rural Systems Engineering, College of Agriculture and Life Sciences, Seoul National University) ;
  • Jun, Sang-Min (Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University) ;
  • Jang, Jeongyeol (Rural Research Institute, Korea Rural Community Corporation) ;
  • Song, Inhong (Department of Rural Systems Engineering, College of Agriculture and Life sciences, Research Institute of Green Bio Science and Technology, Global Smart Farm Convergence Major, Seoul National University) ;
  • Kang, Moon-Seong (Department of Rural Systems Engineering, College of Agriculture and Life Sciences, Research Institute of Green Bio Science and Technology, Seoul National University) ;
  • Choi, Jin-Yong (Department of Rural Systems Engineering, College of Agriculture and Life sciences, Research Institute of Green Bio Science and Technology, Global Smart Farm Convergence Major, Seoul National University)
  • Received : 2021.03.25
  • Accepted : 2021.07.02
  • Published : 2021.07.31
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Abstract

Determining design rainfall is the first step to plan an agricultural drainage facility. The objective of this study is to evaluate whether the current method for parameter estimation is reasonable for computing the design rainfall. The current Gumbel-Kendall (G-K) method was compared with two other methods which are Gumbel-Chow (G-C) method and Probability weighted moment (PWM). Hourly rainfall data were acquired from the 60 ASOS (Automated Synoptic Observing System) stations across the nation. For the goodness-of-fit test, this study used chi-squared (𝛘2) and Kolmogorov-Smirnov (K-S) test. When using G-K method, 𝛘2 statistics of 18 stations exceeded the critical value (𝑥2a=0.05,df=4=9.4877) and 10, 3 stations for G-C method, PWM method respectively. For K-S test, none of the stations exceeded the critical value (Da=0.05n=0.19838). However, G-K method showed the worst performances in both tests compared to other methods. Subsequently, this study computed design rainfall of 48-hour duration in 60 ASOS stations. G-K method showed 5.6 and 6.4% higher average design rainfall and 15.2 and 24.6% higher variance compared to G-C and PWM methods. In short, G-K showed the worst performance in goodness-of-fit tests and showed higher design rainfall with the least robustness. Likewise, considering the basic assumptions of the design rainfall estimation, G-K is not an appropriate method for the practical use. This study can be referenced and helpful when revising the agricultural drainage standards.

Keywords

Acknowledgement

이 논문은 2020년도 정부 (과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임 (No. 2017R1E1A1A01077413).

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