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Assessment and a review of research on surface water quality modeling

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  • Bai, Jing
  • Zhao, Jian
  • Zhang, Zhenyu
  • Tian, Ziqiang

Abstract

Numerical simulation is an effective way to study the transport and transformation of pollutants in surface water bodies. Widely used models include AQUATOX, CE-QUAL-W2, Delft3D, EFDC, MIKE, and WASP. Published reviews or articles concerning these models were selected via a series of queries to the Web of Science. The review was conducted from both a macro and a micro perspective. The time trends and regional variations of these models’ applications were investigated using CiteSpace. CE-QUAL-W2 and EFDC were the top two models used in publications and citations. The country most frequently using surface water quality models was the USA, followed by China. Descriptions, applications, and comparisons of the selected models are explained in detail. Model coupling is an important trend in surface water quality modeling. The goal of this study is to help researchers easily identify studies from a particular region. Central research themes and comparisons of water quality models will help users in the selection of appropriate models in water quality assessment and management practices.

Suggested Citation

  • Bai, Jing & Zhao, Jian & Zhang, Zhenyu & Tian, Ziqiang, 2022. "Assessment and a review of research on surface water quality modeling," Ecological Modelling, Elsevier, vol. 466(C).
    • Handle: RePEc:eee:ecomod:v:466:y:2022:i:c:s0304380022000151
    DOI: 10.1016/j.ecolmodel.2022.109888
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    Cited by:

    1. Hanane Rhomad & Karima Khalil & Khalid Elkalay, 2023. "Water Quality Modeling in Atlantic Region: Review, Science Mapping and Future Research Directions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 451-499, January.
    2. Chen, Xiang-nan & Li, Fang & Wu, Feng-ping & Xu, Xia & Zhao, Yue, 2023. "Initial water rights allocation of Industry in the Yellow River basin driven by high-quality development," Ecological Modelling, Elsevier, vol. 477(C).
    3. Shaogeng Zhang & Junqiang Lin & Youkun Li & Boran Zhu & Di Zhang & Qidong Peng & Tiantian Jin, 2024. "Water Quality by Spectral Proper Orthogonal Decomposition and Deep Learning Algorithms," Sustainability, MDPI, vol. 17(1), pages 1-25, December.

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