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Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents by stochastic analysis

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Abstract

Identifying source information after river chemical spill occurrences is critical for emergency responses. However, the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated. To fill this gap, stochastic analysis approaches, including a regional sensitivity analysis method, identifiability plot and perturbation methods, were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework. Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules. For example, the release load can be most easily inverted, and the source location is responsible for the largest uncertainty among the source parameters. The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty. The differences among the different objective functions are smaller for instantaneous release than for continuous release cases. Small monitoring errors affect the inversion results only slightly, which can be ignored in practice. Interestingly, the estimated values of the release location and time negatively deviate from the real values, and the extent is positively correlated with the relative size of the mixing zone to the objective river reach. These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.

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Acknowledgements

This work was funded by the China Postdoctoral Science Foundation (Grant No.2014M551249) and the National Natural Science Foundation of China (Grant No.51509061). Additional support was provided by the Southern University of Science and Technology (Grant No. G01296001). Jiping Jiang wishes to thank Dr. Bin Shi and Dr. Jie Liu for profiles organization and manuscript edit, and thank Dr. Aiqing Huang for decision support system development. We are also grateful for constructive comments from anonymous reviewers.

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Authors and Affiliations

  1. School of Environment, Harbin Institute of Technology, Harbin, 150090, China

    Jiping Jiang & Yixing Yuan

  2. School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 581055, China

    Jiping Jiang, Feng Han & Yi Zheng

  3. School of Mechanical Engineering, Beijing Institute of Petrochemical Technology, Beijing, 102617, China

    Nannan Wang

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  1. Jiping Jiang
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Correspondence to Jiping Jiang.

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Jiang, J., Han, F., Zheng, Y. et al. Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents by stochastic analysis. Front. Environ. Sci. Eng. 12, 6 (2018). https://doi.org/10.1007/s11783-018-1081-4

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  • DOI: https://doi.org/10.1007/s11783-018-1081-4

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