• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.107-119
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• 2020

This study analyzed past drought characteristics based on the observed rainfall data and performed a long-term outlook for future extreme droughts using Representative Concentration Pathways 8.5 (RCP 8.5) climate change scenarios. Standardized Precipitation Index (SPI) used duration of 1, 3, 6, 9 and 12 months, a meteorological drought index, was applied for quantitative drought analysis. A single long-term time series was constructed by combining daily rainfall observation data and RCP scenario. The constructed data was used as SPI input factors for each different duration. For the analysis of meteorological drought observed relatively long-term since 1954 in Korea, 12 rainfall stations were selected and applied 10 general circulation models (GCM) at the same point. In order to analyze drought characteristics according to climate change, trend analysis and clustering were performed. For non-stationary frequency analysis using sampling technique, we adopted the technique DEMC that combines Bayesian-based differential evolution ("DE") and Markov chain Monte Carlo ("MCMC"). A non-stationary drought frequency analysis was used to derive Severity-Duration-Frequency (SDF) curves for the 12 locations. A quantitative outlook for future droughts was carried out by deriving SDF curves with long-term hydrologic data assuming non-stationarity, and by quantitatively identifying potential drought risks. As a result of performing cluster analysis to identify the spatial characteristics, it was analyzed that there is a high risk of drought in the future in Jeonju, Gwangju, Yeosun, Mokpo, and Chupyeongryeong except Jeju corresponding to Zone 1-2, 2, and 3-2. They could be efficiently utilized in future drought management policies.

• Korean Journal of Environmental Biology
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• v.32 no.4
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• pp.286-296
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• 2014

In this study, we investigated the macrobenthic community structure and spatiotemporal variations in Uljin Marine Ranching area, East Sea of Korea. Macrobenthos were collected using a modified van Veen grab sampler from April to September 2013. Total number of species sampled was 345 and mean density was 5,797 ind. $m^{-2}$, both of which were dominated by the polychaetes. The most dominant species were Spiophanes bombyx (53.64%), followed by Magelona sp.1 (6.96%), Cadella semitorta (2.73%), Lumbrineris longifolia (2.16%) and Alvenius ojianus (2.08%). Cluster analysis and nMDS ordination analysis based on the Bray-Curtis similarity identified 2 station groups. The group 1 (station 2, 3, 5, 6, 8 and 9) was characterized by high abundance of the polychaetes Magelona sp.1, Lumbrineris longifolia, Scoloplos armiger, Praxillella affinis, Maldane cristata and the bivalve Alvenius ojianus, with fine sediment above 30m water depth. On the other hand, the group 2 (station 1, 4, 7 and 10) was numerically dominated by the polychaete Lumbrineriopsis sp. and the bivalve Cadella semitorta, with coarse sediment below 5m water depth. Collectively, the macrobenthic community structure showed a distinct spatial trend, which seemed to be related to the water depth and sediment composition.