为了定量探究典型城市暴雨径流管理模型（SWMM）中水文水力参数的全局灵敏度，利用基于方差分解的Sobol方法，计算不同雨强下SWMM中各参数对径流量、峰值流量以及峰现时间的灵敏度，简要分析结果的收敛性. 研究结果表明，在不同雨强下，SWMM中水文水力模块的灵敏参数及相关排序有所差异. 在大雨强条件下，不渗透地区表面的曼宁糙率对3类输出变量都是最灵敏参数，总阶灵敏度均大于0.6；混凝土管段的曼宁糙率系数对峰现时间的灵敏度远大于对其他2类输出变量的灵敏度. 在小雨强条件下，无洼地蓄水不渗透性百分比为灵敏参数，不渗透性地面洼地储蓄为最灵敏参数，第1阶灵敏度指数为0.396. 在模型前63 000次运行中，计算得到的Sobol指数上下波动，在运行84 000次之后，Sobol指数逐渐趋于收敛.%The Sobol method based on variance decomposition was used to calculate the sensitivity of parameters in the storm water management model (SWMM) to runoff, peak flow, and peak time under two different rainfall conditions, and the convergence of the results was briefly analyzed, in order to quantitatively explore the global sensitivity of hydro-hydraulic parameters in the typical urban SWMM. Results showed that the sensitive parameters and relative ranking of hydro-hydraulic modules in SWMM were different under different rainfall intensities. The impervious areas’ Manning roughness was the most sensitive parameter for all three kinds of output variables under the heavy rainfall intensity condition, and the total sensitivity values were all greater than 0.6. The Manning roughness coefficient of the concrete pipe section was much more sensitive to the peak time than to the other two types of output variables. Percent of impervious area with no depression storage was sensitive parameter, and the impervious ground surface store was the most sensitive parameter with the first-order sensitivity index of 0.396 in the small rainfall intensity condition. The calculated Sobol indexes fluctuated in the first 63 000 runs of the model and tended to converge after 84 000 runs.
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