Research paper Spatio-temporal analysis of extreme precipitation regimes across South Korea and its application to regionalization Jeong-Ju Lee a , Hyun-Han Kwon b, * , Tae-Woong Kim c a Water Resources Investigation & Planning Dept., K-water, Daejeon, South Korea b Department of Civil Engineering, Chonbuk National University, 664-14 1Ga Deokjin-Dong, Jeonju-City, Jeonbuk 561-756, South Korea c Department of Civil and Environmental Engineering, Hanyang University, Ansan 426-791, South Korea Received 16 March 2011; revised 20 October 2011; accepted 28 November 2011 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 K- means 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. Ó 2012 International Association for Hydro-environment Engineering and Research, Asia Pacific Division. Published by Elsevier B.V. All rights reserved. Keywords: Circular statistics; Spatio-temporal analysis; Regional frequency analysis 1. Introduction We used hydrologic frequency analysis to produce guid- ance about the expected behavior of a specified event. The underlying assumption is that hydrologic events are random variables and are stationary, meaning that the statistical properties of hydrologic events will not change in the future. Estimation of the frequency of extreme events is often of particular interest, and point frequency analysis using a single set of data is well established. However, uncertainties associ- ated with limited sample size in an “on site” analysis are a well documented problem in existing literature (Andres et al., 2007; Faustini and Kaufmann, 2007). Statistically homogeneous samples of data are of particular interest in hydrologic frequency analysis, and these may be observations of the same variables scrutinized by multiple sources in terms of measuring sites and instruments. If extremes from multiple sources are statistically similar, more robust estimates can be expected by pooling all data, and this is a regionalization approach. Frequency analysis in conjunc- tion with regionalization is known as regional frequency analysis in hydrological applications. * Corresponding author. E-mail address: hkwon@jbnu.ac.kr (H.-H. Kwon). Available online at www.sciencedirect.com Journal of Hydro-environment Research 6 (2012) 101e110 www.elsevier.com/locate/jher 1570-6443/$ - see front matter Ó 2012 International Association for Hydro-environment Engineering and Research, Asia Pacific Division. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.jher.2012.01.002