High spatial and temporal variation in precipitation in South Korea leads to an increase in the frequency and duration of drought. In this study, the spatial characteristics of temporal trends for precipitation and drought severity time series were analyzed at 55 stations across South Korea for the period 1980-2015. This study also reviewed the usefulness of different trend tests while addressing the issue of serial correlation, which has often received less attention in previous studies. Results showed that most significant trends in precipitation were detected along the south coast of South Korea, especially during winter, late spring and summer, whereas no significant trend was detected in annual precipitation. The Sen's slope of the trends increased from January to August and decreased from August onward. Principal component analysis applied on Standardized Precipitation Index (SPI) at a 12-month time scale divides the whole of South Korea into four subregions with different temporal behaviors of drought severity. Moreover, drought severity showed a significant increasing trend, mainly on the northeast coast. Drought frequency analysis showed more frequent droughts in late winter, early spring and early autumn, with less frequent droughts in summer.

In South Korea, meteorological droughts are becoming frequently-occurring phenomena in different parts of the country, because precipitation varies significantly in both space and time. In this study, the quantiles of four identified homogeneous regions were estimated by incorporating major drought variables (e.g., duration and severity) based on the Standardized Precipitation Index (SPI). The regional frequency analysis of drought was performed by evaluating a variety of probability distributions and copulas, using graphical comparisons and goodness-of-fit test statistics. Results indicate that the Pearson type III (PE3) and Kappa marginal distributions, as well as Gaussian and Frank copulas, are better able to simulate the drought variables across the region. Bivariate stochastic simulation of selected copulas showed that the behavior of simulated data may change when the degree of association (e.g., Kendall's τ) between the drought variables was considered. Results showed that the southwest coast and east coastal areas are under high drought risk, and inland mid-latitude areas (surrounding areas of Yeongju station) and northwest parts are under low drought risk. The joint distributions were used to compute conditional probabilities, as well as primary, secondary, and conditional return periods, which can be useful for designing and managing water demand and the supply system on a regional scale.

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Topographic and hydro-climatic features of South Korea are highly heterogeneous and able to influence the drought phenomena in the region. The complex topographical and hydro-climatic features of South Korea need a statistically accurate method to find homogeneous regions. Regionalization of drought in a bivariate framework has scarcely been applied in South Korea before. Hierarchical Classification on Principal Components (HCPC) algorithm together with Principal Component Analysis (PCA) method and cluster validation indices were investigated and used for the regionalization of drought across the South Korean region. Statistical homogeneity and discordancy of the region was tested on univariate and bivariate frameworks. HCPC indicate that South Korea should be divided into four regions which are closer to being homogeneous. Univariate and bivariate homogeneity and discordancy tests showed the significant difference in their results due to the inability of univariate homogeneity and discordancy measures to consider the joint behavior of duration and severity. Regionalization of drought for SPI time scale of 1, 3, 6, 12, and 24 months showed significant variation in discordancy and homogeneity of the region with the change in SPI time scale. The results of this study can be used as basic data required to establish a drought mitigation plan on regional scales.

Abstract:Since the climatic features of South Korea are highly complex and time variable, spatio-temporal-based drought frequency analysis is a prerequisite for drought risk management. The spatial extent of drought risk analysis in a bivariate framework has scarcely been applied in South Korea before. In this study, the spatio-temporal changes in drought events are investigated at 55 stations across South Korea during 1980-2015. A variety of probability distributions and copulas are applied, and the best fitted is selected on the basis the goodness of fit. The spatial distributions of primary and secondary return periods showed a high risk of drought due to the unusual precipitation pattern in the western coast areas and at Uljin station and a relative low risk of drought in the northwestern portion and surrounding areas of Yeongju, Uiseong, Boeun and Daejeon stations. Overall, the spatial distribution patterns of primary and secondary (Kendall) return periods are similar. However, their applicability changes according to the type of drought risk to be considered. The spatio-temporal quantification of the return period can be used for establishing the proper water demand and supply system and helps to overcome the challenges faced in the hydrometeorological regulations of reservoirs in the southwest coast.