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Modeling of Turbidity Variation in Two Reservoirs Connected by a Water Transfer Tunnel in South Korea

Author

Listed:
  • Jae Chung Park

    (Andong Regional Office, K-water, Andong-si, Gyeongsangbuk-do 36611, Korea)

  • Myoung-Jin Um

    (Department of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Korea)

  • Young-Il Song

    (Division of Climate Change and Interdisciplinary Research, Korea Environment Institute, Sejong 30147, Korea)

  • Hyun-Dong Hwang

    (Human Planet Corporation, Daejeon 34077, Korea)

  • Mun Mo Kim

    (Department of Civil Engineering, Shingu University, Seongnam-si, Gyeonggi-do 13174, Korea)

  • Daeryong Park

    (Department of Civil, Environmental and Plant Engineering, Konkuk University, Seoul 05029, Korea)

Abstract

The Andong and Imha reservoirs in South Korea are connected by a water transfer tunnel. The turbidity of the Imha reservoir is much higher than that of the Andong reservoir. Thus, it is necessary to examine the movement of turbidity between the two reservoirs via the water transfer tunnel. The aim of this study was to investigate the effect of the water transfer tunnel on the turbidity behavior of the two connecting reservoirs and to further understand the effect of reservoir turbidity distribution as a function of the selective withdrawal depth. This study applied the CE-QUAL-W2, a water quality and 2-dimensional hydrodynamic model, for simulating the hydrodynamic processes of the two reservoirs. Results indicate that, in the Andong reservoir, the turbidity of the released water with the water transfer tunnel was similar to that without the tunnel. However, in the Imha reservoir, the turbidity of the released water with the water transfer tunnel was lower than that without the tunnel. This can be attributed to the higher capacity of the Andong reservoir, which has double the storage of the Imha reservoir. Withdrawal turbidity in the Imha reservoir was investigated using the water transfer tunnel. This study applied three withdrawal selections as elevation (EL.) 141.0 m, 146.5 m, and 152.0 m. The highest withdrawal turbidity resulted in EL. 141.0 m, which indicates that the high turbidity current is located at a vertical depth of about 20–30 m because of the density difference. These results will be helpful for understanding the release and selective withdrawal turbidity behaviors for a water transfer tunnel between two reservoirs.

Suggested Citation

  • Jae Chung Park & Myoung-Jin Um & Young-Il Song & Hyun-Dong Hwang & Mun Mo Kim & Daeryong Park, 2017. "Modeling of Turbidity Variation in Two Reservoirs Connected by a Water Transfer Tunnel in South Korea," Sustainability, MDPI, vol. 9(6), pages 1-16, June.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:6:p:993-:d:101020
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    References listed on IDEAS

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    1. F. Gökbulak & Y. Serengil & S. Özhan & N. Özyuvacı & N. Balcı, 2008. "Effect of Timber Harvest on Physical Water Quality Characteristics," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(5), pages 635-649, May.
    2. Ma, Jun & Liu, Defu & Wells, Scott A. & Tang, Hongwu & Ji, Daobin & Yang, Zhengjian, 2015. "Modeling density currents in a typical tributary of the Three Gorges Reservoir, China," Ecological Modelling, Elsevier, vol. 296(C), pages 113-125.
    3. Jae Chung Park & Young-Il Song & Yong Moon Jung & Sang Jin Song & Daeryong Park, 2015. "Assessment of the environmental, social and economic benefits of a water transfer tunnel in the Nakdong River, Korea," International Journal of Water Resources Development, Taylor & Francis Journals, vol. 31(4), pages 618-629, December.
    4. C. Iglesias & J. Martínez Torres & P. García Nieto & J. Alonso Fernández & C. Díaz Muñiz & J. Piñeiro & J. Taboada, 2014. "Turbidity Prediction in a River Basin by Using Artificial Neural Networks: A Case Study in Northern Spain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 319-331, January.
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