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2021 Vol.63, Issue 4 Preview Page
Evaluation of Parameter Estimation Method for Design Rainfall Estimation

설계강우량 산정을 위한 매개변수 추정방법 평가

Kwihoon Kima
,
Sang-Min Junb
,
Jeongyeol Jangc
,
Inhong Songd
,
Moon-Song Kange
,
Jin-Yong Choif†
김 귀훈a
,
전 상민b
,
장 정렬c
,
송 인홍d
,
강 문성e
,
최 진용f†
aPh.D. Student, Department of Rural Systems Engineering, College of Agriculture and Life Sciences, Seoul National University
bResearch Professor, Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University
cPrincipal Researcher, Rural Research Institute, Korea Rural Community Corporation
dAssociate Professor, 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
eProfessor, Department of Rural Systems Engineering, College of Agriculture and Life Sciences, Research Institute of Green Bio Science and Technology, Seoul National University
fProfessor, 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
a서울대학교 농생명대학 농촌시스템공학과 박사과정 학생
b서울대학교 농생명과학대학 연구교수
c한국농어촌공사 농촌연구원 주임연구원
d서울대학교 농업생명과학대학 농촌시스템공학부 부교수, 녹색생명과학기술연구원, 글로벌 스마트팜 융합전공
e서울대 농생명과학원 농촌시스템공학과 교수
f서울대학교 농업생명과학대학 농촌시스템공학부 교수, 녹색바이오과학기술원 글로벌스마트팜융합전공
† Corresponding author Tel.: +82-2-880-4583, Fax: +82-2-873-2087 E-mail: iamchoi@snu.ac.kr
2021. pp. 87-95
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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 (=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 (=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
Design rainfall
parameter estimation
goodness-of-fit test
References

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Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 63
  • No :4
  • Pages :87-95
  • Received Date : 2021-03-25
  • Revised Date : 2021-05-31
  • Accepted Date : 2021-06-02
  • DOI :https://doi.org/10.5389/KSAE.2021.63.4.087
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