4.7 Article

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

Journal

WATER RESOURCES MANAGEMENT
Volume 35, Issue 12, Pages 3915-3935

Publisher

SPRINGER
DOI: 10.1007/s11269-021-02883-7

Keywords

Input uncertainty; The uncertainty interaction; Hydrological model; Jialing river basin

Funding

  1. Joint Funds of the National Science Foundation of China [U1965202]
  2. National Natural Science Foundation of China [51879214]

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The study investigates the impacts of rain gauge station input levels and hydrological models on flows with different magnitudes. Different input levels and models dynamically affected hydrological simulation, with better accuracy at high flow and poor accuracy at low flow. Increasing the number of rainfall stations input under a certain threshold significantly improved the simulation accuracy.
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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