• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.389-398
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• 2006

The present study compositely applied the self-organizing map (SOM), which is a kind of artificial neural networks (ANNs), and the back propagation algorithm (BPA) for the rainfall-runoff prediction model taking account of the irregular variation of the spatiotemporal distribution of rainfall. To solve the problems from the previous studies on ANNs, such as the overestimation of low flow during the dry season, the underestimation of runoff during the flood season and the persistence phenomenon, in which the predicted values continuously represent the preceding runoffs, we introduced SOM theory for the preprocessing in the prediction model. The theory is known that it has the pattern classification ability. The method proposed in the present research initially includes the classification of the rainfall-runoff relationship using SOM and the construction of the respective models according to the classification by SOM. The individually constructed models used the data corresponding to the respectively classified patterns for the runoff prediction. Consequently, the method proposed in the present study resulted in the better prediction ability of runoff than that of the past research using the usual application of ANNs and, in addition, there were no such problems of the under/over-estimation of runoff and the persistence.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.446-454
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• 2023

The impact of climate change on agriculture is substantial, especially as global warming is projected to lead to varying temperature and humidity patterns in the future. These changes pose a higher risk for both crops and livestock, exposing them to environmental stressors under altered climatic conditions. Specifically, as temperatures are expected to rise, the risk of heat stress is assessable through the Temperature-Humidity Index (THI), derived from temperature and relative humidity data. This study involved the comparison of THI collected from 10 Korea Meteorological Administration ASOS stations spanning a 60-year period from 1961 to 2020. Moreover, high-resolution temperature and humidity distribution data from 1981 to 2020 were employed to generate high-resolution TH I distributions, analyzing temporal changes. Additionally, the number of days characterized by heat stress, derived from TH I, was compared over different time periods. Generally, TH I showed an upward trend over the past, albeit with varying rates across different locations. As TH I increased, the frequency of heat stress days also rose, indicating potential future cost increases in the livestock industry due to heat-related challenges. The findings emphasize the feasibility of evaluating heat stress risk in livestock using THI and underscore the need for research analyzing THI under future climate change scenarios.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.720-734
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• 2023

To understand the spatiotemporal distribution pattern of zooplankton and the environmental factors influencing zooplankton abundance in Gomso Bay, major harvesting area of Manila clam (Venerupis philippinarum) in South Korea, zooplankton sampling was conducted four times in autumn (October 2022), winter (January 2023), early spring (March 2023), and spring (May 2023). Among the environmental factors of Gomso Bay, water temperature, chlorophyll a concentration (Chl-a), dissolved oxygen (DO), and pH observed different patterns, while salinity and suspended particulate matter(SPM) showed no significant statistical differences between the survey periods. The zooplankton in Gomso Bay occurred 33, 29, 27, and 29 taxonomic groups during each respective survey period. In October 2022 and May 2023, arthropod plankton were dominated, while in January and March 2023, protozoa were primarily dominant. Among the Arthropods, copepods including Acartia hongi, Paracalanus parvus s. l., Corycaeus spp., and Oithona spp. commonly found along Korean coastal areas of the Yellow Sea, were dominated. Cluster analysis based on zooplankton abundance indicated a single community (stable condition) in each season, attributed to low dissimilarity distances, while three distinct clusters (autumn, winter-early spring, spring) between seasons indicated a highly seasonal environment in Gomso Bay.

• Korean Journal of Environment and Ecology
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• v.33 no.6
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• pp.654-663
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• 2019

Pollinators, which are important organisms in pollination ecology, have been highly valued for their economic contributions to crop production in the agricultural and biotechnology industries. As the production of over 70% of farm products, such as fruits, are mediated by pollinators, bees are important and useful insects to humans. However, pollinators are now seriously threatened with their numbers decreasing annually and their biodiversity being negatively affected by ongoing climate change, misuse of land, change of geographical features, and use of pesticides to increase agricultural production. Thus, surveys and analyses of the emergence and distribution of wild bees are important for conservation and management practices designed to help them continue to play their ecological and agricultural roles despite negative pressures, such as climate and topography changes. We surveyed pollinators, especially wild bees, at 51 research sites in South Korea every two to four weeks for two years from 2017 to 2018 using ez-Malaise traps and analyzed the temporal and spatial distribution of wild bees. The bees showed a normal temporal distribution that peaked between July and August. The bees' working period lasted until November. The spatial distribution of wild bees showed a significant correlation with latitude, and different bees were identified depending on the local habitat. No significant correlation was found for longitudinal distribution with regression analysis (p > 0.05), but this study identified locally specific wild bees. Although we could not predict significant distribution according to longitude, Further studies should be able to analyze the difference in the distribution of wild bees according to the climate, topography, and land-use patterns by humans. The results of this study provide basic information on pollinator distribution, which can be useful in agriculture and for the conservation and management of biodiversity in South Korean pollination ecology.

• Journal of the Korean Society for Marine Environment & Energy
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• v.17 no.2
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• pp.131-145
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• 2014

The new passive sampler called "artificial mussel (AM)" offers a potential device to study the spatiotemporal changes of metal concentrations in different marine environment worldwide. The purpose of this study is to characterize metal (Cd, Cr, Cu, Zn, Pb) accumulation on the AM and transplanted mussel (Mytilus edulis) at 5 sites of Lake Shihwa. Both the AMs and mussels showed increasing concentrations of all five metals during the 12 weeks exposure period. Higher concentrations of Zn were showed in both the AMs and Mytilus edulis relative to other metals. The AMs accumulated higher concentrations of Cd, Cr and Zn, but they presented lower levels of Cu and Pb than Mytilus edulis. The correlations for Cd, Cu and Pb were statistically significant between the AMs and Mytilus edulis, indicating that the accumulation patterns for those metals were similar. However, no similarities for Cr and Zn were observed between two monitoring devices across all of the sites in Shihwa Lake. According to relationship for metal concentrations between dissolve phase in seawater and both the AMs and Mytilus edulis, the AMs for Cd, Cu and Zn represent more metal contamination than Mytilus edulis. Our results indicated that the AMs give a better resolution to reveal the spatial differences in dissolved metal concentration. This study suggests that the AMs can provide a time-integrated estimate of metal pollution in marine environments as well as freshwater environments of Korea.