Multiple uncertainty sources directly cause inaccurate simulations for water related processes in complicated integrated models, as such models include many interactive modules. A majority of existing studies focus on the uncertainties of parameter and model structure, and their effects on the model performance for a single process (e.g., hydrological cycle or water quality). However, comprehensive uncertainties of different modules and their propagations are poorly understood, particularly for the integrated water system model. This study proposes a framework of uncertainty and its propagation estimation for integrated water system model (HEQM) by coupling the Bootstrap resampling method and SCE-UA auto-calibration technique. Parameter and structure uncertainties of both hydrological cycle and water quality modules are estimated, including final distributions of parameters and simulation uncertainty intervals. Additionally, the effect of uncertainty propagation of hydrological parameters is investigated. Results show that: (1) HEQM simulates daily hydrograph very well with the coefficient of efficiency of 0.81, and also simulates the daily concentrations of ammonia nitrogen satisfactorily with the coefficient of efficiency of 0.50 by auto-calibration in the case study area; (2) The final ranges of all interested hydrological parameters are reduced obviously, and all the parameter distributions are well-defined and show skew. The uncertainty intervals of runoff simulation at the 95% confidence level bracket 18.7% of all the runoff observations due to uncertainties of parameter, and 86.0% due to both parameter and module structure, respectively; (3) The uncertainty propagation of hydrological parameters changes the optimal values of 37.5% of interested water quality parameters, but does not obviously change the water quality simulations which match well with the prior simulations throughout the period and bracket only 1.7% of observations at the 95% confidence level. Due to the further introduction of module structure uncertainties, 94.8% of observations are bracketed, only except the extreme high and low water quality concentrations; (4) The uncertainty of water quality parameters contributes 12.1% of total water quality simulations at the 95% confidence level. The figure increases to 21.0% and 92.0% if the uncertainty propagation of hydrological parameters, structure uncertainties of water quality module are considered, respectively. Therefore, although the parameter uncertainty and its propagation contribute a certain proportion of the whole simulation uncertainties, the module structure itself is the primary uncertainty source for the integrated water system model (HEQM), particular for the water quality modules.
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