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The development of a multi-species algal ecodynamic model for urban surface water systems and its application

Author

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  • Jia, Haifeng
  • Zhang, Yansong
  • Guo, Yu

Abstract

An ecodynamic model that can simulate four phytoplankton species has been developed to deal with the unique characteristics of urban river systems which has manmade river profile, flow controlled by gates, severe eutrophication status, and fragile aquatic ecosystem. The ecodynamic model was developed referencing two typical models: the water quality simulation model WASP and ecological model CAEDYM. The model can simulate 11 state variables: dissolved oxygen, carbonaceous biochemical oxygen demand, ammonia nitrogen, nitrate nitrogen, organic nitrogen, inorganic phosphorus, organic phosphorus and four phytoplankton species with zooplankton as a boundary condition. The ecodynamic model was applied to Sihai section of the Beijing urban river system, where serious algal blooms broke out in recent years. The dominant phytoplankton species are Cyanophyta, Chlorophyta, Bacillariophyta, and Cryptophyta. Site-specific data on geometry, meteorology, pollution sources, and existing ecosystem parameters were collected and used for model calibration and verification The model results mimic observed trends of water quality and phytoplankton species succession and can be used for forecasting algal blooms as well as assessment of river management measures.

Suggested Citation

  • Jia, Haifeng & Zhang, Yansong & Guo, Yu, 2010. "The development of a multi-species algal ecodynamic model for urban surface water systems and its application," Ecological Modelling, Elsevier, vol. 221(15), pages 1831-1838.
    • Handle: RePEc:eee:ecomod:v:221:y:2010:i:15:p:1831-1838
    DOI: 10.1016/j.ecolmodel.2010.04.009
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    Cited by:

    1. Niu, Zhiguang & Gou, Qianqian & Wang, Xiujun & Zhang, Ying, 2016. "Simulation of a water ecosystem in a landscape lake in Tianjin with AQUATOX: Sensitivity, calibration, validation and ecosystem prognosis," Ecological Modelling, Elsevier, vol. 335(C), pages 54-63.
    2. 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.
    3. Bae, Sunim & Seo, Dongil, 2021. "Changes in algal bloom dynamics in a regulated large river in response to eutrophic status," Ecological Modelling, Elsevier, vol. 454(C).
    4. Bae, Soonyim & Seo, Dongil, 2018. "Analysis and modeling of algal blooms in the Nakdong River, Korea," Ecological Modelling, Elsevier, vol. 372(C), pages 53-63.
    5. Ertürk, Ali & Sakurova, Ilona & Zilius, Mindaugas & Zemlys, Petras & Umgiesser, Georg & Kaynaroglu, Burak & Pilkaitytė, Renata & Razinkovas-Baziukas, Artūras, 2023. "Development of a pelagic biogeochemical model with enhanced computational performance by optimizing ecological complexity and spatial resolution," Ecological Modelling, Elsevier, vol. 486(C).

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