关键词: 耦合模型, 水沙演进, 模型参数, 全局敏感性分析, 黄河下游

Abstract: Some parameters used in the numerical simulations of fluvial process are usually determined empirically, but their effects have not been examined quantitatively in previous studies. This paper describes a 1D morphodynamic model based on the dynamical coupling of flow and sediment transport, and discusses its simulations of flood routing processes in the lower Yellow in the 2020 flood season. Simulation results indicate (i) time variations in water level and discharge are accurately reproduced, with Nash-Sutcliffe Efficiency Coefficients (NSEs) larger than 0.85 and RMSEs less than 15% of the corresponding mean values. (ii) Although the simulated peak sediment concentration is larger than its measured value, an insignificant difference exists in the patterns of simulated and measured hydrographs. (iii) The calculated volume of riverbed deformation is close to its value measured using the method of cross-sectional riverbed topography. The global sensitivity analysis method proposed by Sobol is adopted to evaluate the effects of some input parameters on the simulations, by taking the NSEs of hydrological indicators at the hydrometric stations as the objective functions. Our findings indicate the importance of an input factor depends on the choice of objective functions. Comparison of sensitivity indexes calculated using different objective functions reveals comprehensive roughness is most sensitive among all the input parameters. When the objective function is the NSE of sediment concentration, the parameters of higher first-order index and total index values are the coefficient of the sediment transport capacity formula and the exponent for recovery coefficient calculation. Generally, a certain parameter combination has quite different sensitivity behaviors under different objective functions, while different parameter combinations could generate comparable effects under the same objective function. Global sensitivity analysis demonstrates the individual effects of different parameters and their interactive effects on the model results, helping improve model calibration for simulations of fluvial process.

Key words: 1D coupled model, flood routing process, model parameters, global sensitivity analysis, lower Yellow River