Spatio-temporal analysis of extreme precipitation regimes across South Korea and its application to regionalization
- Authors
- Lee, Jeong-Ju; Kwon, Hyun-Han; Kim, Tae-Woong
- Issue Date
- May-2012
- Publisher
- Elsevier BV
- Keywords
- Circular statistics; Spatio-temporal analysis; Regional frequency analysis
- Citation
- Journal of Hydro-Environment Research, v.6, no.2, pp 101 - 110
- Pages
- 10
- Indexed
- SCIE
SCOPUS
- Journal Title
- Journal of Hydro-Environment Research
- Volume
- 6
- Number
- 2
- Start Page
- 101
- End Page
- 110
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/33062
- DOI
- 10.1016/j.jher.2012.01.002
- ISSN
- 1570-6443
1876-4444
- Abstract
- Assessing spatio-temporal variability of extreme rainfall is required to establish future plans and policies for water resource management. One of the main objectives of this study is to introduce an effective approach based on circular statistics for assessing the seasonality of the extreme precipitation. Circular statistics explicitly reflect the seasonal pattern of precipitation with maximum frequency of the timing of daily and monthly maximums. In southern Korea, a dominant frequency was identified in early July. The timing of the monthly maximum has been delayed in northern Korea. In the case of the daily maximum, the end of June is the period of most intense rainfall, with the exception of the east coast near Gangrung. A long-term temporal variation of timed monthly and daily maximums was investigated by a 30-year moving average for main stations. Monthly peak times of Seoul and Gangrung continuously moved backward while monthly peak times of Mokpo and Busan has moved forward since the 1960's. These features could be influenced by inherent variations in the East Asian monsoon system. Given the identified spatio-temporal pattern, this study was extended to characterize regional patterns of extreme rainfall over Korea. A new concept in regionalization procedures was developed on the basis of existing approaches that mainly utilize simple moments of data. In this study, the Kmeans method was incorporated with the temporal pattern of the extreme rainfalls in order to better characterize hydrologic patterns for regional frequency analysis. The results showed that the proposed approach is promising for the region in term improving the physical understanding of extreme rainfall. (C) 2012 International Association for Hydra-environment Engineering and Research, Asia Pacific Division. Published by Elsevier B.V. All rights reserved.
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