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http://dx.doi.org/10.7837/kosomes.2020.26.1.065

The Prediction of Hypoxia Occurrence in Dangdong Bay  

Kang, Hoon (Department of Civil & Environmental Engineering, Kunsan National University)
Kwon, Min Sun (Department of Civil & Environmental Engineering, Kunsan National University)
You, Sun Jae (Department of Civil & Environmental Engineering, Kunsan National University)
Kim, Jong Gu (Department of Civil & Environmental Engineering, Kunsan National University)
Publication Information
Journal of the Korean Society of Marine Environment & Safety / v.26, no.1, 2020 , pp. 65-74 More about this Journal
Abstract
The purpose of this study was to investigate the physical characteristics of marine environment, and to predict the probability of the occurrence of hypoxia in the Dangdong bay. We predicted hypoxia using the logistic regression model analysis by observing the water temperature, salinity, and dissolved oxygen concentration. The analysis showed that the Brunt-Väisälä frequency which was shallow than the deep bay entrance, was higher inside the bay due to a lesser amount of fresh water inflow from the inner side of the bay, and density stratification was formed. The Richardson number, and Brunt-Väisälä frequency were very high occasionally from June to September; however, after September 2, the stratification had a tendency to decrease. Analysis of dissolved oxygen, water temperature, and salinity data observed in Dangdong bay showed that the dissolved oxygen concentration in the bottom layer was mostly affected by the temperature difference (dt) between the surface layer and bottom layer. Meanwhile, when the depth difference (dz) was set as a fixed variable, the probability of the occurrence of hypoxia varied with respect to the difference in water temperature. The depth difference (dz) was calculated to be 5 m, 10 m, 15 m, 20 m, and the difference in water temperature (dt) was found to be greater than 70 % at 8℃, 7℃, 5℃, and 3℃. This indicated that the larger the difference in depth in the bay, the smaller is the temperature difference required for the generation of hypoxia. In particular, the place in the bay, where the water depth dif erence was approximately 20 m, was found to generate hypoxia.
Keywords
Hypoxia; Logistic regression model; Dissolved oxygen; Density; Water temperature; Salinity;
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