Drainage-system management relies on results from urban stormwater models; errors in these models may have serious implications. Inaccurate field data or overly simplified models may cause the complex response of an urban basin to a rainfall event to be inadequately represented. Before undertaking expensive studies to gather and analyze additional data, it is reasonable to understand what enhancement in model performance would result if individual uncertainties could be decreased. This paper uses data collected during field monitoring campaigns to calibrate and validate a hydrologic and sediment-transport model within the Storm Water Management Model (SWMM). Solid accumulation and disappearance rates were identified as factors generating the highest model sensitivity. A generalized evaluation matrix is presented that considers both the uncertainty in input variables and the associated sensitivity in model response to inform model performance expectations and guide investments in model improvement toward actions with maximum benefit.

排水系统管理依赖于城市雨水模型的结果。这些模型中的错误可能会产生严重的影响。不准确的现场数据或过于简化的模型可能会导致城市流域对降雨事件的复杂响应无法充分体现。在进行昂贵的研究以收集和分析其他数据之前，有必要先了解一下，如果可以减少单个不确定性，将会导致模型性能的提高。本文使用在野外监测活动中收集的数据来校准和验证雨水管理模型（SWMM）中的水文和泥沙输送模型。固体积累和消失率被确定为产生最高模型灵敏度的因素。