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Uncertainty analysis for integrated water system simulations using GLUE with different acceptability thresholds

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Abstract

Integrated water quantity and quality simulations have become a popular tool in investigations on global water crisis. For integrated and complex models, conventional uncertainty estimations focus on the uncertainties of individual modules, e.g., module parameters and structures, and do not consider the uncertainties propagated from interconnected modules. Therefore, this study investigated all the uncertainties of integrated water system simulations using the GLUE (i.e., generalized likelihood uncertainty estimation) method, including uncertainties associated with individual modules, propagated uncertainties associated with interconnected modules, and their combinations. The changes in both acceptability thresholds of GLUE and the uncertainty estimation results were also investigated for different fixed percentages of total number of iterations (100000). Water quantity and quality variables (i.e., runoff and ammonium nitrogen) were selected for the case study. The results showed that module uncertainty did not affect the runoff simulation performance, but remarkably weakened the water quality responses as the fixed percentage increased during calibration and validation periods. The propagated uncertainty from hydrological modules could not be ignored for water quality simulations, particularly during validation. The combination of module and propagated uncertainties further weakened the water quality simulation performance. The uncertainty intervals became wider owing to an increase in the fixed percentages and introduction of more uncertainty sources. Moreover, the acceptability threshold had a negative nonlinear relationship with the fixed percentage. The fixed percentages (∼20.0%–30.0%) were proposed as the acceptability thresholds owing to the satisfactory simulation performance and noticeably reduced uncertainty intervals they produced. This study provided methodological foundations for estimating multiple uncertainty sources of integrated water system models.

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Authors and Affiliations

  1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    YongYong Zhang & Jun Xia

  2. CSIRO Data 61, Wembley, Western Australia, 6913, Australia

    QuanXi Shao

  3. Bjerknes Centre for Climate Research, NORCE Norwegian Research Centre, Bergen, 5007, Norway

    Lu Li

  4. Blackland Research and Extension Center, Texas A&M University, Temple, Texas, 76502, USA

    Haw Yen

  5. China Institute of Water Resources and Hydropower Research, Beijing, 100038, China

    XiaoYan Zhai

  6. Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou, 510275, China

    TongTieGang Zhao & KaiRong Lin

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  1. YongYong Zhang
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Correspondence to YongYong Zhang.

Additional information

This work was supported by the National Natural Science Foundation of China (Grant Nos. 42071041 and 41807171), and the Outstanding Youth Science Foundation of the National Natural Science Foundation of China (Grant No. 51822908). Thanks to the Huaihe Valley Ecology and Environment Administration, Ministry of Ecology and Environment for offering the water quality data.

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Zhang, Y., Xia, J., Shao, Q. et al. Uncertainty analysis for integrated water system simulations using GLUE with different acceptability thresholds. Sci. China Technol. Sci. 64, 1791–1804 (2021). https://doi.org/10.1007/s11431-020-1752-0

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  • DOI: https://doi.org/10.1007/s11431-020-1752-0

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