Hydrologic Modeling for Simulation of Rainfall-Runoff at Major Control Points of Geum River Watershed

Kim, Hyung-San; Azam, Muhammad; Maeng, Seung-Jin

doi:10.1016/j.proeng.2016.07.545

Cited by 5 publications

(7 citation statements)

References 3 publications

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“…Region IV is spread mainly along the northeast coast of South Korea. Delineation of Region IV for the SPI-time scales (1,3,6,12, and 24 months) indicate that the number of stations varies from 12 to 13. Topographical and hydro-climatic features of this region are extremely complex as compared to other regions.…”

Section: Discussionmentioning

confidence: 99%

“…Region II is the smallest region and delineated for the SPI-time scales (1,3,6,12, and 24 months). The number of stations in this region varies from 4 to 6 and occupies the mid-latitude inland of South Korea.…”

Section: Bivariate Regionalization Of Drought Across South Koreamentioning

confidence: 99%

“…Region III delineated for the SPI-time scales (1,3,6,12, and 24 months) are spread mainly along the north-east side of South Korea. The number of stations varies from 18 to 21.…”

Section: Bivariate Regionalization Of Drought Across South Koreamentioning

confidence: 99%

“…Recent variation of climate on an interdecadal time scale due to global warming across South Korea has had a large impact on agriculture production and water resource management [1], and may cause floods [2,3] and drought conditions. The occurrence of extreme drought events has increased abruptly in the East Asian region since 1980 [4].…”

Section: Introductionmentioning

confidence: 99%

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Regionalization of Drought across South Korea Using Multivariate Methods

Azam

Park

Maeng

et al. 2017

Water

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Bivariate Regionalization Of Drought Across South Koreamentioning

confidence: 99%

“…Region III delineated for the SPI-time scales (1,3,6,12, and 24 months) are spread mainly along the north-east side of South Korea. The number of stations varies from 18 to 21.…”

Section: Bivariate Regionalization Of Drought Across South Koreamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Regionalization of Drought across South Korea Using Multivariate Methods

Azam

Park

Maeng

et al. 2017

Water

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“…A bivariate distribution should be derived to express the correlated drought variables. In the case of flood studies, bivariate normal distributions [11], bivariate exponential distributions [12] and bivariate gamma distributions [13] or rainfall-runoff hydrological models [14,15] are often applied. The major drawbacks of these bivariate distributions are that the individual behavior of random variables must be characterized by the same parametric family of univariate distributions [16].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Changes in Spatio-Temporal Patterns of Drought across South Korea

Maeng

Azam

Kim³

et al. 2017

Water

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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.

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