Abstract
Eutrophication models are of great importance and are valuable tools for the development of policy and legislation. However, the parameter uncertainty and substantial computational cost lead to difficulties in decision-making, especially for complex models with multiple indicators. A multicriteria uncertainty analysis and parameter estimation (MUAPE) method, which selected behavioral parameters combined with Pareto domination and simultaneously obtained acceptable values for modeling by the maximum likelihood concept and kernel density estimation, was shown. This method, which did not assign thresholds and weights, was applied to analyze the uncertainty of the Chaohu Lake eutrophication model and estimate parameters. The results of the behavioral parameters were compared using different criterion sets, the relative error (RE) and the root mean square error (RMSE), and the results showed little discrepancy in terms of the effects on parameter uncertainty represented by the marginal probability density. The uncertainties of the parameters related to algal kinetics (i.e., BMR, PM, and KESS) were smaller than those of nutrient- and temperature-related parameters (i.e., KDN, Nitm, KTB, and KTHDR) for both sets of criteria. However, the reduction in the joint uncertainty of the two parameters was greater when RE was used than when RMSE was used. The acceptable values for the key parameters of the Chaohu Lake eutrophication model were also obtained by the RE criterion. The results strongly agreed with the observed values, and parameters could be applied for model prediction. This result indicated that the combination method was not only practical for reducing parameter uncertainty but also useful for determining parameter values. This method provides a basis for multicriteria uncertainty analysis and parameter estimation in eutrophication modeling.
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Acknowledgments
We also thank the editors and all anonymous reviewers for their constructive comments that greatly improved this manuscript.
Funding
This study was financially supported by the Major Science and Technology Program for Water Pollution Control and Treatment (Grant No. 2012ZX07103-005), the National Key R & D Program of China (Grant No. 2017YFC0403205), the National Natural Science Foundation of China (Grant Nos. 51909230, 51809226, 51739002), the China Postdoctoral Science Foundation funded project (Grant No. 2019 M661948), the Jiangsu Planned Projects for Postdoctoral Research Funds (Grant Nos. 2018K124C), and the Jiangsu Funded the Recruitment of Postdoctoral Project (Grant No. 2018Z051, 2019Z319).
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Wang, Y., Cheng, H., Wang, L. et al. A combination method for multicriteria uncertainty analysis and parameter estimation: a case study of Chaohu Lake in Eastern China. Environ Sci Pollut Res 27, 20934–20949 (2020). https://doi.org/10.1007/s11356-020-08287-1
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DOI: https://doi.org/10.1007/s11356-020-08287-1