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Three-dimensional numerical modeling of the cyanobacterium Microcystis transport and its population dynamics in a large freshwater reservoir

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  • Liu, Haidong
  • Zheng, Zhongquan C.
  • Young, Bryan
  • Harris, Ted D.

Abstract

Cyanobacterial blooms pose severe ecological and economical threats in lakes and reservoirs. Understanding the complex physical transport and biological features of cyanobacteria (also known as blue-green algae) is important for predicting blooms in freshwater systems. In this study, a three-dimensional model for nonhydrostatic free surface flow and Microcystis sp. (cyanobacteria) transport and associated population dynamics is presented. The hydrodynamic model solves the Reynolds-averaged Navier-Stokes equations using a semi-implicit, fractional time-step finite difference method. The hydrodynamic model can couple Microcystis transport to a population dynamics model that simulates buoyancy, vertical migration, and effects of temperature, light, nutrients, and salinity on the concentration of Microcystis. Microcystis transport was determined by solving the convection-diffusion equation. The vertical migration of Microcystis was simulated based on buoyancy density changes of a colony at a given depth and time due to irradiance. The transient Microcystis production at a given depth was calculated based on the effects of different environmental factors such as depth, irradiance, and temperature. The model was used to analyze the transport and growth of Microcystis in Milford Lake, which is the largest man-made lake in Kansas. Transport and population dynamics of Microcystis under different environmental conditions were simulated, and the effects of different environmental factors were compared in a 20-hour test. Overall, physical processes like wind mixing most effected Microcystis distribution throughout the simulation; when wind was low, water column turbidity effected Microcystis distribution more than temperature or ambient light. This study is the first 3D nonhydrostatic free surface flow computational model that includes Microcystis transport, buoyancy regulation/vertical migration, and population dynamics. Nonhydrostatic models are needed because existing ecological models with hydrostatic approximation can be ill-posed when dealing with open boundaries, and hydrostatic approximation is not valid when dealing with flow over rapidly changing slopes. The current model is a robust and efficient way to model Microcystis transport and can be applied to studies of other surface water systems effectively.

Suggested Citation

  • Liu, Haidong & Zheng, Zhongquan C. & Young, Bryan & Harris, Ted D., 2019. "Three-dimensional numerical modeling of the cyanobacterium Microcystis transport and its population dynamics in a large freshwater reservoir," Ecological Modelling, Elsevier, vol. 398(C), pages 20-34.
    • Handle: RePEc:eee:ecomod:v:398:y:2019:i:c:p:20-34
    DOI: 10.1016/j.ecolmodel.2019.01.022
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    References listed on IDEAS

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    1. Wu, Guozheng & Xu, Zongxue, 2011. "Prediction of algal blooming using EFDC model: Case study in the Daoxiang Lake," Ecological Modelling, Elsevier, vol. 222(6), pages 1245-1252.
    2. Wang, Chao & Feng, Tao & Wang, Peifang & Hou, Jun & Qian, Jin, 2017. "Understanding the transport feature of bloom-forming Microcystis in a large shallow lake: A new combined hydrodynamic and spatially explicit agent-based modelling approach," Ecological Modelling, Elsevier, vol. 343(C), pages 25-38.
    3. Aparicio Medrano, E. & van de Wiel, B.J.H. & Uittenbogaard, R.E. & Dionisio Pires, L.M. & Clercx, H.J.H., 2016. "Simulations of the diurnal migration of Microcystis aeruginosa based on a scaling model for physical-biological interactions," Ecological Modelling, Elsevier, vol. 337(C), pages 200-210.
    4. Aparicio Medrano, E. & Uittenbogaard, R.E. & Dionisio Pires, L.M. & van de Wiel, B.J.H. & Clercx, H.J.H., 2013. "Coupling hydrodynamics and buoyancy regulation in Microcystis aeruginosa for its vertical distribution in lakes," Ecological Modelling, Elsevier, vol. 248(C), pages 41-56.
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    1. Zhang, Peng & Li, Kefeng & Liu, Qingyuan & Zou, Qingping & Liang, Ruifeng & Qin, Leilei & Wang, Yuanming, 2024. "Thermal stratification characteristics and cooling water shortage risks for pumped storage reservoir–green data centers under extreme climates," Renewable Energy, Elsevier, vol. 229(C).

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