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Sensitivity Analysis of Urban Landscape Lake Transparency Based on Machine Learning in Taiyuan City

Author

Listed:
  • Yuan Zhou

    (College of Environmental Science and Engineering, Taiyuan University of Technology, Jinzhong 030600, China)

  • Yongkang Lv

    (State Key Laboratory of Clean and Efficient Coal Utilization, Taiyuan University of Technology, Taiyuan 030024, China)

  • Jing Dong

    (College of Environmental Science and Engineering, Taiyuan University of Technology, Jinzhong 030600, China)

  • Jin Yuan

    (College of Environmental Science and Engineering, Taiyuan University of Technology, Jinzhong 030600, China
    Coshare Energy Environment, Taiyuan 030002, China)

  • Xiaomei Hui

    (College of Environmental Science and Engineering, Taiyuan University of Technology, Jinzhong 030600, China)

Abstract

This article addresses the challenge of maintaining water quality in urban landscape lakes in water-scarce cities using transparency as the key indicator. The sensitivity of water transparency to nine water quality parameters, including chlorophyll a and inorganic suspended solids, in 16 urban landscape lakes of the city of Taiyuan was evaluated using the Sobol and Morris sensitivity analysis methods. The results indicate that for water bodies supplied by surface water, critical factors include chlorophyll a and hydraulic retention time. For water bodies supplied by tap water, inorganic suspended solids and total phosphorus are more significant. Water bodies with a dual function of urban flood control should focus on dissolved oxygen, ammonium nitrogen, and chemical oxygen demand. Based on these findings, targeted management strategies are proposed to enhance algae management, control suspended solids input, and adjust water retention times, aiming to improve the transparency and quality of Taiyuan’s urban landscape.

Suggested Citation

  • Yuan Zhou & Yongkang Lv & Jing Dong & Jin Yuan & Xiaomei Hui, 2024. "Sensitivity Analysis of Urban Landscape Lake Transparency Based on Machine Learning in Taiyuan City," Sustainability, MDPI, vol. 16(16), pages 1-18, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:16:p:7026-:d:1457389
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    References listed on IDEAS

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    1. Jiang, Long & Li, Yiping & Zhao, Xu & Tillotson, Martin R. & Wang, Wencai & Zhang, Shuangshuang & Sarpong, Linda & Asmaa, Qhtan & Pan, Baozhu, 2018. "Parameter uncertainty and sensitivity analysis of water quality model in Lake Taihu, China," Ecological Modelling, Elsevier, vol. 375(C), pages 1-12.
    2. Borgonovo, E., 2007. "A new uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 771-784.
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