Abstract
Extreme rainfalls in South Korea result mainly from convective storms and typhoon storms during the summer. A proper way for dealing with the extreme rainfalls in hydrologic design is to consider the statistical characteristics of the annual maximum rainfall from two different storms when determining design rainfalls. Therefore, this study introduced a mixed generalized extreme value (GEV) distribution to estimate the rainfall quantile for 57 gauge stations across South Korea and compared the rainfall quantiles with those from conventional rainfall frequency analysis using a single GEV distribution. Overall, these results show that the mixed GEV distribution allows probability behavior to be taken into account during rainfall frequency analysis through the process of parameter estimation. The resulting rainfall quantile estimates were found to be significantly smaller than those determined using a single GEV distribution. The difference of rainfall quantiles was found to be closely correlated with the occurrence probability of typhoon and the distribution parameters.
| Original language | English |
|---|---|
| Pages (from-to) | 1143-1153 |
| Number of pages | 11 |
| Journal | Stochastic Environmental Research and Risk Assessment |
| Volume | 27 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2013 Jul 1 |
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Keywords
- Extreme rainfall
- Frequency analysis
- Mixed distribution
- Rainfall quantile
ASJC Scopus subject areas
- Environmental Engineering
- Environmental Science(all)
- Environmental Chemistry
- Water Science and Technology
- Safety, Risk, Reliability and Quality
Cite this
Rainfall frequency analysis using a mixed GEV distribution : A case study for annual maximum rainfalls in South Korea. / Yoon, Philyong; Kim, Tae Woong; Yoo, Chulsang.
In: Stochastic Environmental Research and Risk Assessment, Vol. 27, No. 5, 01.07.2013, p. 1143-1153.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Rainfall frequency analysis using a mixed GEV distribution
T2 - A case study for annual maximum rainfalls in South Korea
AU - Yoon, Philyong
AU - Kim, Tae Woong
AU - Yoo, Chulsang
PY - 2013/7/1
Y1 - 2013/7/1
N2 - Extreme rainfalls in South Korea result mainly from convective storms and typhoon storms during the summer. A proper way for dealing with the extreme rainfalls in hydrologic design is to consider the statistical characteristics of the annual maximum rainfall from two different storms when determining design rainfalls. Therefore, this study introduced a mixed generalized extreme value (GEV) distribution to estimate the rainfall quantile for 57 gauge stations across South Korea and compared the rainfall quantiles with those from conventional rainfall frequency analysis using a single GEV distribution. Overall, these results show that the mixed GEV distribution allows probability behavior to be taken into account during rainfall frequency analysis through the process of parameter estimation. The resulting rainfall quantile estimates were found to be significantly smaller than those determined using a single GEV distribution. The difference of rainfall quantiles was found to be closely correlated with the occurrence probability of typhoon and the distribution parameters.
AB - Extreme rainfalls in South Korea result mainly from convective storms and typhoon storms during the summer. A proper way for dealing with the extreme rainfalls in hydrologic design is to consider the statistical characteristics of the annual maximum rainfall from two different storms when determining design rainfalls. Therefore, this study introduced a mixed generalized extreme value (GEV) distribution to estimate the rainfall quantile for 57 gauge stations across South Korea and compared the rainfall quantiles with those from conventional rainfall frequency analysis using a single GEV distribution. Overall, these results show that the mixed GEV distribution allows probability behavior to be taken into account during rainfall frequency analysis through the process of parameter estimation. The resulting rainfall quantile estimates were found to be significantly smaller than those determined using a single GEV distribution. The difference of rainfall quantiles was found to be closely correlated with the occurrence probability of typhoon and the distribution parameters.
KW - Extreme rainfall
KW - Frequency analysis
KW - Mixed distribution
KW - Rainfall quantile
UR - http://www.scopus.com/inward/record.url?scp=84878610880&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84878610880&partnerID=8YFLogxK
U2 - 10.1007/s00477-012-0650-5
DO - 10.1007/s00477-012-0650-5
M3 - Article
AN - SCOPUS:84878610880
VL - 27
SP - 1143
EP - 1153
JO - Stochastic Environmental Research and Risk Assessment
JF - Stochastic Environmental Research and Risk Assessment
SN - 1436-3240
IS - 5
ER -