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Changes in Hydraulics–Water Quality–Bloom–Aquatic Habitat Using an Integrated Chain Modeling and Artificial Intelligence Technique in the Yeongsan River

Author

Listed:
  • Byungwoong Choi

    (Water Environment Research Department, National Institute of Environmental Research, Incheon 22689, Republic of Korea)

  • Jonghwan Park

    (Yeongsan River Environment Research Center, National Institute of Environmental Research, Gwangju 61011, Republic of Korea)

  • Tae-Woo Kang

    (Yeongsan River Environment Research Center, National Institute of Environmental Research, Gwangju 61011, Republic of Korea)

  • Don-Woo Ha

    (Yeongsan River Environment Research Center, National Institute of Environmental Research, Gwangju 61011, Republic of Korea)

  • Seong-Yun Hwang

    (Yeongsan River Environment Research Center, National Institute of Environmental Research, Gwangju 61011, Republic of Korea)

  • Won-Seok Lee

    (Yeongsan River Environment Research Center, National Institute of Environmental Research, Gwangju 61011, Republic of Korea)

  • Eunhye Na

    (Water Environment Research Department, National Institute of Environmental Research, Incheon 22689, Republic of Korea)

  • Jiyeon Choi

    (Yeongsan River Environment Research Center, National Institute of Environmental Research, Gwangju 61011, Republic of Korea)

Abstract

This study utilized the Delft3D and HABITAT models to investigate the impact of environmental changes resulting from various weir operation scenarios on aquatic habitats and ecosystem health. The weirs were configured to operate with their sluice gates either fully or partially open. The Delft3D model effectively predicted the dominance of diatoms and green algae due to physicochemical changes in weir operation, replicating adaptive processes such as algal growth, competition, and succession. The model indicated a transition to diatom dominance when weirs were fully open and green algae became abundant. The analysis of aquatic ecosystem health in this study, focusing on habitat changes using the HABITAT model, revealed an improvement in aquatic ecosystem health by one level, even with a single weir sluice gate fully open. Furthermore, the utilization of all input variables in the prediction of algae, through the application of artificial intelligence technology, considerably improved prediction accuracy when compared with selectively employing variables with high correlations to changes in chlorophyll-a concentration. These findings underscore the significance of considering various weir operation scenarios and employing advanced modeling techniques to effectively manage and maintain the health of aquatic ecosystems in the face of environmental changes.

Suggested Citation

  • Byungwoong Choi & Jonghwan Park & Tae-Woo Kang & Don-Woo Ha & Seong-Yun Hwang & Won-Seok Lee & Eunhye Na & Jiyeon Choi, 2023. "Changes in Hydraulics–Water Quality–Bloom–Aquatic Habitat Using an Integrated Chain Modeling and Artificial Intelligence Technique in the Yeongsan River," Sustainability, MDPI, vol. 15(23), pages 1-17, November.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:23:p:16355-:d:1289201
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    References listed on IDEAS

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    1. Minha Lee & Heejung Kim & Jin-Yong Lee & Jae E. Yang & Chungwan Lim, 2022. "A Shift Towards Integrated and Adaptive Water Management in South Korea: Building Resilience Against Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(5), pages 1611-1625, March.
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