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A Water Quality Model with Three Dimensional Variational Data Assimilation for Contaminant Transport

Author

Listed:
  • Dongguo Shao

    (Wuhan University)

  • Zhuomin Wang

    (Wuhan University)

  • Bei Wang

    (Wuhan University)

  • Weiwei Luo

    (Wuhan University)

Abstract

The safety of water delivery and water quality in the South to North Water Transfer Project is important to China. When sudden pollution accidents happen in this project, a high-accuracy water quality model is needed to simulate contaminant transport. Data assimilation algorithm can be used to improve the accuracy of model, and a water quality model with three dimensional variational data assimilation (3DVAR-WQM), are developed in this paper. A contaminant transport experiment has been conducted for verifying the feasibility and accuracy of this model. After analyzing the simulated results in 3DVAR-WQM and the standard water quality model without assimilation, it has been found that the model with simulation estimates the arrival time and value of the peak concentration more accurately, and that the error between the simulated and observed data in this model is little. At the same time, the root mean square error of this model are smaller. This paper increases forecasting skills through data assimilation techniques, and it provides a tool for improving water quality management in the South to North Water Transfer Project of China.

Suggested Citation

  • Dongguo Shao & Zhuomin Wang & Bei Wang & Weiwei Luo, 2016. "A Water Quality Model with Three Dimensional Variational Data Assimilation for Contaminant Transport," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4501-4512, October.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:13:d:10.1007_s11269-016-1432-5
    DOI: 10.1007/s11269-016-1432-5
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    References listed on IDEAS

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    1. Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
    2. Gift Dumedah, 2012. "Formulation of the Evolutionary-Based Data Assimilation, and its Implementation in Hydrological Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(13), pages 3853-3870, October.
    3. Wenquan Gu & Dongguo Shao & Yufang Jiang, 2012. "Risk Evaluation of Water Shortage in Source Area of Middle Route Project for South-to-North Water Transfer in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(12), pages 3479-3493, September.
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    Cited by:

    1. Xizhi Nong & Dongguo Shao & Yi Xiao & Hua Zhong, 2019. "Spatio-Temporal Characterization Analysis and Water Quality Assessment of the South-to-North Water Diversion Project of China," IJERPH, MDPI, vol. 16(12), pages 1-23, June.

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