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Quantifying the Uncertainty Interaction Between the Model Input and Structure on Hydrological Processes

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A Correction to this article was published on 06 September 2021

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Abstract

Input error is one of the main sources of uncertainty in hydrological models. It mainly comes from the uncertainty of precipitation data, which is caused by inaccurate measurement at the point scale and imperfect representation at the regional scale. The structural error of the hydrological model is dependent on the input, and the uncertainty interaction between the model input and structural will increase the cumulative error of the hydrological process. Therefore, the objective of this study is to investigate the impacts of the uncertainties of rain gauge station input levels and hydrological models on flows with different magnitudes by setting nine input levels of rain gauge stations using three hydrological models (i.e., HyMod, XAJ and HBV). The variance decomposition method based on subsampling was used to dynamically quantify the contribution rates of rain gauge station input levels, hydrological models, and their interaction to the runoff simulation uncertainty. The results show that different rain gauge station input levels and hydrological models dynamically affected the hydrological simulation due to an uneven spatiotemporal distribution of precipitation. Moreover, the simulation accuracy was poor at low flow but better at high flow. Increasing the number of rainfall stations input under a certain threshold could significantly improve the hydrological simulation accuracy. In addition, the contributions of the uncertainties of the rain gauge station input levels and its interaction with the hydrological model to runoff were significantly enhanced in the flood season, but the contribution of the hydrological model uncertainty was still dominant. The results of this study can provide a decision-making basis and scientific guidance for the management and planning of water resources within basins under the influence of a changing environment.

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Funding

This work was supported by Joint Funds of the National Science Foundation of China (Grant numbers U1965202) and National Natural Science Foundation of China (Grant numbers, 51879214).

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Authors and Affiliations

  1. State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an, China

    Shuai Zhou, Yimin Wang, Ziyan Li, Jianxia Chang & Aijun Guo

Authors
  1. Shuai Zhou
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  2. Yimin Wang
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  3. Ziyan Li
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  4. Jianxia Chang
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  5. Aijun Guo
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Contributions

All authors contributed to the study conception and design. Shuai Zhou: Writing—Original draft preparation, Conceptualization, Methodology, Software. Yimin Wang: Conceptualization, Methodology, Reviewing and Editing. Ziyan Li: Methodology, Software, Editing. Jianxia Chang: Visualization, Investigation, Supervision, Editing. Aijun Guo: Software, Validation.

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Correspondence to Yimin Wang.

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It is our honor to publish our research in Water Resources Management, and of course, all the authors agree to publish this research in Water Resources Management.

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The original online version of this article was revised: In this article the affiliation details for Author Yimin Wang was incorrectly given as 'Xian University' but should have been 'Xi’an University of Technology'

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Zhou, S., Wang, Y., Li, Z. et al. Quantifying the Uncertainty Interaction Between the Model Input and Structure on Hydrological Processes. Water Resour Manage 35, 3915–3935 (2021). https://doi.org/10.1007/s11269-021-02883-7

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