Journal of Korean Society on Water Environment (한국물환경학회지)

Korean Society on Water Environment (한국물환경학회)
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Projection of water temperature and stratification strength with climate change in Soyanggang Reservoir in South Korea

기후변화에 따른 소양호 수온 및 성층강도 변화 예측

  • Yun, Yeojeong (Department of Environmental Engineering, Chungbuk National University) ;
  • Park, Hyungseok (Department of Environmental Engineering, Chungbuk National University) ;
  • Chung, Sewoong (Department of Environmental Engineering, Chungbuk National University)
  • Received : 2019.02.26
  • Accepted : 2019.05.02
  • Published : 2019.05.30
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Abstract

In a deep lake and reservoir, thermal stratification is of great importance for characteristics of hydrodynamic mixing of the waterbody, and thereby influencesvertical distribution of dissolved oxygen, substances, nutrients, and the phytoplankton community. The purpose of this study, was to project the effect of a future climate change scenario on water temperature, stratification strength, and thermal stability in the Soyanggang Reservoir in the Han River basin of South Korea, using a suite of mathematical models; SWAT, HEC-ResSim, and CE-QUAL-W2(W2). W2 was calibrated with historical data observed 2005-2015. Using climate data generated by HadGEM2-AO with the RCP 4.5 scenario, SWAT predicted daily reservoir inflow 2016-2070, and HEC-ResSim simulated changes in reservoir discharge and water level, based on inflow and reservoir operation rules. Then, W2 was applied, to predict long-term continuous changes of water temperature, in the reservoir. As a result, the upper layer (5 m below water surface) and lower layer (5 m above bottom) water temperatures, were projected to rise $0.0191^{\circ}C/year$(p<0.05) and $0.008^{\circ}C/year$(p<0.05), respectively, in response to projected atmospheric temperature rise rate of $0.0279^{\circ}C/year$(p<0.05). Additionally, with increase of future temperature, stratification strength of the reservoir is projected to be stronger, and the number of the days when temperature difference of the upper layer and the lower layer becomes greater than $5^{\circ}C$, also increase. Increase of water temperature on the surface of the reservoir, affected seasonal growth rate of the algae community. In particular, the growth rate of cyanobacteria increased in spring, and early summer.

Keywords

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Fig. 1. Locations of the study area and research point

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Fig. 2. Flowchart of the modeling processes, used in this study.

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Fig. 3. Comparison of simulated reservoir water level and capacity curve with observed one.

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Fig. 4. Comparison of observed and simulated (a) water level and (b) water temperature

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Fig. 5. Comparison of observed and simulated water temperature profiles (2007)

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Fig. 6. Historical (2005-2015), and projected (2016-2070) monthly water temperature, at the upper and lower layer in Soyanggang Reservoir.

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Fig. 7. Projected seasonal variations of annual water temperatures, at the upper and lower layer of the reservoir, in the future.

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Fig. 8. Calender heatmap showing averaged daily water temperature 2005-2070, at the (a) upper layer and the (b) lower layer.

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Fig. 9. (a) Schmidt stability 2016-2070 and (b) number of stratification formation days.

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Fig. 10. (a) Temperature dependence of growth rates for phytoplankton groups, (b) comparison of monthly phytoplankton growth rates between historical and projected periods.

Table 1. Statistical indices used to evaluate the model accuracy

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Table 2. Average air temperature and reservoir water temperature, at the upper and lower layer in Soyanggang Reservoir, for historical and projection periods.

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Table 3. Monthly historical and projected upper water temperatures and their difference.

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Table 4. Monthly historical and projected lower water temperatures and their difference.

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Table 5. Seasonal upper and lower water temperature and rise rate (2016~2070)

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Table 6. Seasonal upper-lower water temperature differences (2016 ~ 2070)

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Table 7. Average water temperature on the specified date 2005-2070, at the upper and lower layers

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Table 8. Parameters used for calculating the growth rate of each phytoplankton group

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Table 9. Comparison of growth rates of each phytoplankton group as a function of water temperature between historical and projected periods.unit: /d

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